{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "# 语义分割和数据集\n",
    "\n",
    "最重要的语义分割数据集之一是[Pascal VOC2012](http://host.robots.ox.ac.uk/pascal/VOC/voc2012/)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "origin_pos": 4,
    "tab": [
     "pytorch"
    ]
   },
   "outputs": [],
   "source": [
    "%matplotlib inline\n",
    "import os\n",
    "import torch\n",
    "import torchvision\n",
    "from d2l import torch as d2l\n",
    "\n",
    "d2l.DATA_HUB['voc2012'] = (d2l.DATA_URL + 'VOCtrainval_11-May-2012.tar',\n",
    "                           '4e443f8a2eca6b1dac8a6c57641b67dd40621a49')\n",
    "\n",
    "voc_dir = d2l.download_extract('voc2012', 'VOCdevkit/VOC2012')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "将所有输入的图像和标签读入内存"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "origin_pos": 7,
    "tab": [
     "pytorch"
    ]
   },
   "outputs": [],
   "source": [
    "def read_voc_images(voc_dir, is_train=True):\n",
    "    \"\"\"读取所有VOC图像并标注。\"\"\"\n",
    "    txt_fname = os.path.join(voc_dir, 'ImageSets', 'Segmentation',\n",
    "                             'train.txt' if is_train else 'val.txt')\n",
    "    mode = torchvision.io.image.ImageReadMode.RGB\n",
    "    with open(txt_fname, 'r') as f:\n",
    "        images = f.read().split()\n",
    "    features, labels = [], []\n",
    "    for i, fname in enumerate(images):\n",
    "        features.append(\n",
    "            torchvision.io.read_image(\n",
    "                os.path.join(voc_dir, 'JPEGImages', f'{fname}.jpg')))\n",
    "        labels.append(\n",
    "            torchvision.io.read_image(\n",
    "                os.path.join(voc_dir, 'SegmentationClass', f'{fname}.png'),\n",
    "                mode))\n",
    "    return features, labels\n",
    "\n",
    "train_features, train_labels = read_voc_images(voc_dir, True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "绘制前5个输入图像及其标签"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "origin_pos": 10,
    "tab": [
     "pytorch"
    ]
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 540x216 with 10 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "n = 5\n",
    "imgs = train_features[0:n] + train_labels[0:n]\n",
    "imgs = [img.permute(1, 2, 0) for img in imgs]\n",
    "d2l.show_images(imgs, 2, n);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "列举RGB颜色值和类名"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "origin_pos": 12,
    "tab": [
     "pytorch"
    ]
   },
   "outputs": [],
   "source": [
    "VOC_COLORMAP = [[0, 0, 0], [128, 0, 0], [0, 128, 0], [128, 128, 0],\n",
    "                [0, 0, 128], [128, 0, 128], [0, 128, 128], [128, 128, 128],\n",
    "                [64, 0, 0], [192, 0, 0], [64, 128, 0], [192, 128, 0],\n",
    "                [64, 0, 128], [192, 0, 128], [64, 128, 128], [192, 128, 128],\n",
    "                [0, 64, 0], [128, 64, 0], [0, 192, 0], [128, 192, 0],\n",
    "                [0, 64, 128]]\n",
    "\n",
    "VOC_CLASSES = [\n",
    "    'background', 'aeroplane', 'bicycle', 'bird', 'boat', 'bottle', 'bus',\n",
    "    'car', 'cat', 'chair', 'cow', 'diningtable', 'dog', 'horse', 'motorbike',\n",
    "    'person', 'potted plant', 'sheep', 'sofa', 'train', 'tv/monitor']"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "查找标签中每个像素的类索引"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "origin_pos": 15,
    "tab": [
     "pytorch"
    ]
   },
   "outputs": [],
   "source": [
    "def voc_colormap2label():\n",
    "    \"\"\"构建从RGB到VOC类别索引的映射。\"\"\"\n",
    "    colormap2label = torch.zeros(256**3, dtype=torch.long)\n",
    "    for i, colormap in enumerate(VOC_COLORMAP):\n",
    "        colormap2label[(colormap[0] * 256 + colormap[1]) * 256 +\n",
    "                       colormap[2]] = i\n",
    "    return colormap2label\n",
    "\n",
    "def voc_label_indices(colormap, colormap2label):\n",
    "    \"\"\"将VOC标签中的RGB值映射到它们的类别索引。\"\"\"\n",
    "    colormap = colormap.permute(1, 2, 0).numpy().astype('int32')\n",
    "    idx = ((colormap[:, :, 0] * 256 + colormap[:, :, 1]) * 256 +\n",
    "           colormap[:, :, 2])\n",
    "    return colormap2label[idx]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "例如"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "origin_pos": 17,
    "tab": [
     "pytorch"
    ]
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(tensor([[0, 0, 0, 0, 0, 0, 0, 0, 0, 1],\n",
       "         [0, 0, 0, 0, 0, 0, 0, 1, 1, 1],\n",
       "         [0, 0, 0, 0, 0, 0, 1, 1, 1, 1],\n",
       "         [0, 0, 0, 0, 0, 1, 1, 1, 1, 1],\n",
       "         [0, 0, 0, 0, 0, 1, 1, 1, 1, 1],\n",
       "         [0, 0, 0, 0, 1, 1, 1, 1, 1, 1],\n",
       "         [0, 0, 0, 0, 0, 1, 1, 1, 1, 1],\n",
       "         [0, 0, 0, 0, 0, 1, 1, 1, 1, 1],\n",
       "         [0, 0, 0, 0, 0, 0, 1, 1, 1, 1],\n",
       "         [0, 0, 0, 0, 0, 0, 0, 0, 1, 1]]),\n",
       " 'aeroplane')"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "y = voc_label_indices(train_labels[0], voc_colormap2label())\n",
    "y[105:115, 130:140], VOC_CLASSES[1]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "使用图像增广中的随机裁剪，裁剪输入图像和标签的相同区域"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "origin_pos": 22,
    "tab": [
     "pytorch"
    ]
   },
   "outputs": [
    {
     "data": {
      "image/png": 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F1RW3bt7l+ePPUb4l50xVVRiV8SXdqLQmxsQmJN73mWfJ8PDQ0a472q7nbNmyN53sQtoYPM6JIW83W16dvmI2n1M3DbPJVLZ3TIEphfcDwQeGYSDEAVdu8O58pERMUZBjOcxd7/mb9z7g6YuXrDctq82a1WLNO29/i6PDOYd7e/Tec3GxxCrYtj2Hx8dMplOyguVq4MbxEbdvHNNMGt7/H/6fb7KdV/saAu+//56gXaWoGocG+j6QUin4IoYsFoMRMaSQ0Fpy69ZYQoi7Q+hzJGdw0XOyeMINk7mY3GOtJgQfeeet28Xxyz6mkkLOQIy9pONK6iTtDCi7/UzRY/RYU4s7I6lQ5JiIhYyglC4OLRGj1EMyibDecnl2yvzuA0KOfPLhp0yPjjHZMfOeFALL1RofIsPgr7WvADFlVq3HGYUxphjbzGq54T/95fskBT/+wXeZArXJ/NnHP2MbEgZwdYVzhqHzxBJwaiVpj1hqMShDREMcdmlg4xzee4nqlCbkjCVxo73kbX8G87usmkP6wbO/N+PG0bzsqypATpesw7CLGmLOxJS/EEnrUgcmBYySdKZGIjatjBj8EqkYa79gzGPKoLm2Q+sLuB0TUlLbUSU9rLD1FD/0qOSBhLNOMiwxSWanRLw2er7XvuKB9iyP3uEFkecvX/HrP3qLxl4B3BSDRNK/DOAWL65yZuRMqejR+asBboy/HOBmIKTIdtPxvE/EDz8k58Sf/+lf8r1fe5eHb73D+tUZ2/Waoe9JWqMLwD09veSD938qacuvkSaHjCoOTWnJIpAKIcRonNHl2UpXz2kIJYtwBSgVCm3MDiQbozBaWMlagXMWZ2yxL1xlQvQIUkCVlLUqtY6cr9KIZafLJY91UsTDJcrP55LNU184a6MjI4mDCsEzxCQBktCr5NyjyNGTciSHQNsHQvzqvX0jh4bW2HpK1pqM5Gd1ztw6OkZvt2inUWZGUhmrnaCLIGG7MYZkI9Ym+smECwy3TUXQnorEq8s1l11iyBmroE6Rg2lFVokXz1/x2WePaKYTeYBz4gff/z51My1IIrNpe5KPmK4npEinIsYYiRBLmiUVFEnK4sx++gF/8/4HLLZrrLJAwgfPxWLJr/9Xv8vs4IA+arI2Jfeb6IeOatKUB0howdYZnHOFPvTmy/uBZ58/ImuJxmwtDs0PsTg5+YwZSblq5Ti6dZeL06eo5MlkmromRi8HohjSlDPKB2btGq0zTGB5ccF7y3O++927OF0y8DmTUsAYA1nSt957jHOCmnJBWqUGphQQBgkZYiARS7qJ8rOgciyklryL2nwILNdbXp6e8vzVOadn5yz+4I+5ffMGP//ZR/zX/81/jVKazxYLfLslpczxjRtXyf5rrJASl9sBbRRWa4ySx2WzbXl6ek5SlvCTnxPjgAZePX8pe2g0pkRKMaQShRVgoTM+Z1TWHN+6z7Dd0i0uUUgUPZ04+mEQQ6A1KUlLSd935MFzUsE2bIk+8unzF1RNXYxBAXLW7CKrxWKBNoaqqamsK0BOwKXWmhQSOQSi96QUyvUZQACN3LNYyFUlMsmZ56/OePT0OcvV+nr7GgKr5QJVUo5fALimLgD3M5TvyDlTVxVKZcIvAbg/9fAkGR4eOdpNT9t1nC875pMGkOpsDEFacnJis1lzenrKbD6naSZMp9MrYJYlEvBDjx/iDuBaY6/O0esAN5tSjki03cBf/eR9nr18xWbbsd6sWC03fOedt7h544DDvX0677m8XGNVZtsNHJ4cM5lMScBi2XHr5JhbN49p6pp/c80zq5TCEKmcADCtlWQJsmRolDFC4HKlJUFpQozCekSXZzbTDx6tJUOpdRa2pEqEkIiA3RXk5X1jiMUJgjGSYtxlpdUVqUeOoKQlx5rp2PiQR1vB+INj2nGsNF/9J6uSPYgBoxJOJaIP9DEzpJJaV1L3S1GXeumvtgVv5tCywgM6SwXGOsut40PuHx1xfnlBuhAvHRkL0ZFQitkKJcSOKPUGrSUN4FMgJs2TZcu+q+m7gW070J+9oH35jGpS47uW84tLNm3PMHiq2vHyfEnTTIgxEcKA1ZrGVaA1y21HRtFUjsvlitn+Pndu32LS1KSUWS7X9H3gz/7ir9n2W/q+J4WIcZImbbctH370Gd99tyYmzcXZGSdHB5ATwXuJZkrkAWOOO1+BljdcnQ8MSQ5hyIkheazShYIESWlUjuSSFJjP9yBFBjJW6VLfMiWaEsen0cSUSBh+Pj3hqXZ8R9cMucOFxOVqQJdapTMKYqCyQuF/8vkjnj5/zsHREfPZlP29PabTmSQlygHdtIMc0m4gJI8xFsqxVglSCoUppokpkiJ8/uQ5f/Anf8p26LE4htDTbnuOjw/5b/+bf87s+IStzyjXMLOO9XIhKaSv4dByynRti9amkA2EKRd8JGvFth14/OKMVICRNg1KK7JWpaVEg9OFzqxJJKk/Zpg1DVNlWKcAdQ1IHQPryNGSyBityRq0DrSu5lP2MZNDQt+TFWw3nheXW3xWWKPR0TNvHIrEerXi/fc/QGnDfG+G1Zo7d+4ymRQgR8SHwLb3mNpLmlaB0mNtKcNY6zWC+EMIXFyu+YM//hOenr6iH66ZGlMaM9lD5/wFgGty5vbRCWy2KGfQI8A1jkRChfwLANdPJiww9NoR9EBF5uXFmvM2MqSMVZkmjwA38+z5KY8+f0wznQrTMmd++IMfUjWTUnuR85lCRHedlBZ0RBtDilHOcGGMqkL66TvPX/7te/zkZz9n2a6xypFzLAB3wY//q99ltr9PH0rqegS4fU/dNMVGJ6wzBeS6a5/ZFKUEkktKVCtNTFkAZ3FWWUNQcr5UidSVNruzmVLCaUXlLGa8XgXWFA+H/FmTySnssg/idCIxlvJ3Hi35mIJUJZ2Yr9i8QH69XYPXGdkg6efRoe2adXaMbUqq0WmDMZoqRmkhClfljm3vkQrL36NDm81m/Pbv/GNyP1CpgXrvgLqe0V68or38kCq0pDGHmhNaZbKPmOhRztL2kWnVMHOWCYoUW2Y6cnmx5pOPn3KyXLJZr9msPWwu2a7OmE4mmBDAR/rVhtn+ATklXjx9SQLOVyuiyuwZy6E1qBhR8xm3HzyQw4vh8ycvuFxccPP4BKU0FxeXVFWNHzqeff6Ioe3RBu6/8zYRRecH/vanP+Ov33uftx++za2732LbtpiS2815JDQAquTQv2atB1sJ600Jes2q9JWQyMqQMWgys8rx9q3bXC4WEhUpQ1IJoxRRA1FLvUcbIAhyVZqkHSFFEhkfE5+eLjBNQ+8DfdeylwNTk9HWcHqx4HK55fxyw+nZKc4afv/3fpd6OoOUCcHTtQO1VejthMVyhasqtNFsthtmsznz2awQXDJhCJyeLfi3f/BHLNs1Xd9TGUvMYmxfnZ7xve+8LalJ72m3W3TtyMnjw3DttBjA0HW8/+f/kSEkbty6wSc//ymNbbhx9z4pKFJEeuZKMTwrvUOTWkk9QirGJeeIAZWZNhUPb9+mdhWvLs/kgVVJzn2SVoPS0SbEgpGRpyQt1seAzZYniy0cDwwx03cDw2ZJ066k3zBlTs8XrLctbdfRti3ffvgW33rwLWLK+H5Aq4z3kdmkYesTF5cLbhwfc355QT2dcnR4yHw2RWnNerkho/n3//5PeH76kt4PhHBNIhOShk4qo7OcOVc5bp8ccu/gkFcX5+TLQo8vADcT8UmN2P5LAFf215f+uierln1X0XcDm3agP33O9sVT6knD0G05v1ywbXsG76nrmlfnK1xdk0aAawyTqiKjWW5blDZU1rBYrb8AcGPKrJZrus7zF3/5t7RDS9d3ZB/RlZQtNtstH374Kd95tyJEdgA350QMnpiFIn9Vp7s2ti1LfltKCKC11AFzkvru2MqgchKwOwJfk0ugKvVeoyRVKyxIXchM40UKM3wHggqjVCmFSsIGVahdnVGNDN8xpVuyRiPTekwhjmIEV60Z4rhMqcPlVAg3XPW4jYzTzMjwzeCzEGCSfB5xs0Lq+VX24A0jtMw0BgYL3XrLcr1mGDzrxSlhs2IytGiraCY1MbTMq5qjugIfySrCZmA+afjhW/fZszU37t7gzovH/Mnzv+T0ccuLn7xi5jTLbU8ms9doaCtWKWOU5s6tY6bzKZVzaCuG53izx9n5AtO1NNOaqTKElFl8/oioNFFb9q2iTpFuKekbszuEidl0go6RujYc7u/x4uxSDHHWhOTLzVf4wYtzCYEUx5YFOVuxpCyuvTKAZtpMaJqa2liUtWhrAI1TGm1g/+CIm4cHxMtzTrs1eix250RSihA9XdKljmDwMRXSgtTapBA+sFr1nLWeqVa065b1NvCzjz/g9Mnn7O3NCd2WzbZl2w1UTYOzjn/5P/0Bg/cMMWKMorGOm7MZ67bD7c/ZOzgiBc96O9CnxI3jA+bTKSEm+m7A+8Dp6RmbzYqu7cgpcnT7JmjNZtPyh3/0J9y4c5uDgyOydtRmLk7huszRshaXl/z7f/Wv6NHUzYT9ZsKDB/c5ff6SjoYQQ+nH0agkdbOjkxNm8xmTqkJbh7ZG0s4h41Sgmk45Or5B3m548fEHmNCiQypAR5GNZfC+EEcUQxZShDUGk6WXSOeB2Cuebs5ojo/w3ZbVsqdbLjj99OfY2mFDIAbPYrVGGUfdNPz855/xyWfPWKzXBBLzyjFRhqOmZuE99777HV6evqIfEp88PcO6R9w+OcEYQ9f2pJTxwfPiyVP6rsNfM0Kbzmb8w3/4+/gE9AMVA9XeIVU9pT1/SXd5hvPtFfLPGasiyid0HFDOsu0Ss7phXlkmQIotcxM5P93wyUdPOL68YL1as90IwO3Wl0wmDTZGzJAY1i17BwfEGHn57BWRzPl6RSSzbyyHzoAP6P09bt2/L84Tw6MnL1guL7kxAtzzC6q6Zuhbnn3+iL7rMQYefPvb+JzohoG/+enP+Kv33ufbb7/DzTv3adsWVRzayGwEcdRfp78PSu3ID6RQGquNgGijLcRMNAGjNSZZyQgUIYKUAlqbXZO1kMcUKRuSUrs+szEVqCgAGhgphAqF0qNTvOrLLB9udF+SiXmt50wrTdd1pBjY29sTz5ehGyKrPshrxUzcbDFNRdU47O5sgNT+ruqhO6Z1RupnjOzov0eHtl5c8PzP/4TnsWV5+RzlLL1WVAjVXBOZmxkMiiFsOT6+ydH8Ngd7B6iU+Z2TY05u7KH7JbN5jVWKZqpofeTP/upv+O4P3uLsvOPOvTk//+g9pkpzYms+e/6EGyeHnNzYJ+YopI8s4ffxySHDEIhNzXR/ysRpNlFTay1F9lI/E5QtBXrTVOL1k6JpasiRyiqaumFoO2m+NELhzgna7ZbZbCKswyiHNedCfgiBECIhxGtHEs5afuvXfsjt27fo2hYS6MkMUPiYCd0W5TeoumLd9iyWlwz9hsmwoW4qrNU4FTg0hiFHjF+zDZpHL1YcHRzw3ft3mStDM68JF1veOzvlL//gP1KplmHoCT4xtZnjvQqnIm5vzn7d0PqBGzdviqSYMfQ+8PzinGHo0X0HJtN0HVZnku8JWRF8xkePd4mkEk4bXrx8xnS+h0qedrmi7zqm85qDvT0ulis637Petjy/OOc3fvzr7B/eoO97qYnEr+fQnDMcnRwyPTimG3qCD2ibWa4v+PDlOQrNfDZhWtV8553v8q23HnLzxg0gsblYoesJbjJFK0MfA6ldEfqW02dPWa0XrM5fMk0eGwb2DqYMXc9h7TgwlhR6nA58+HSNcjUP7t/j3sERhwdzboY9/vYv/5bNKvGnn32Myy2Dl7RdXWX2bMOQoLaGyckR9bRhf3+fnBPWWs4uFpyvN5jtFucUMwsqZIbHj/ApM6CxKCoMuV2TjIW2E+GB5LEKhiT15WutlFB9zxTNYDLb1YbL1YphGFhfnhG3AnCNU9R1RYpbZq8B3KQyahvYc5ofPnzA3FYCcJ8+4k+e/RVnTz7lxU9eMHeWxaYlK9hvNGwdi5Sx2nDn9hHT2ZTKCfhTKI43e5yfL9BdRzNtmKAJGRaPnhCVIhnHgZMafbtcYIzBxEDsM0YlZrMJOkWaiWV/f87z03OUGUipAFyArBgGjyMRC3taayNR0ghwv0ZWIaXEarPFKL1TJ8kZtDFYZwszWUMc62KSUtRJoVUQxSGtJMWrNDpqYhEV2G421PUErTRpECLMxXJDVpXwDcrraaOxWtF7j1LmqjVDyz6jEgYjqcZS+ydE0jDAyzWpAP+PHr8g5oAhUWFwbcfSWe7fvcHRrMEZ+XzWSD3QGI2rLLPpDBXHmi/Ctv7P2NI3cmgxR/785c/oes/RrGbsBw1Z6KI5JwZ/Qdq03L71Fg8P3sI/62nff0L0kc3+Keu3bnHrezfRDcTNBV3vGTYdehv50z99j59+9BF3b9/mxz94QLt5xdPU0Rw6eu35+Mmnkg/PirowyYyxLJcLtHNcLgPaakJ1xOH8uBSsC71VmcJgKoy7ENl0LSkn9o+OqSrL5WpFDBEdIkaZ0jQMzWTGdrXhkw9+wjvvfofjEEHLfvgQ8D7sUNR1VtNUWDxPPn6Pg/191ssNHYq03nJcTznHszh/RTaaIXhy1xOHDuJAjg6FpqoVe80e88khqt7jqKp4990Tbt444sApZpMJewdznj97TN92vNpuUb7lYO+Yj58+5+zVGXuH+wyt55N2w43jA+49uIfSA9aCceBqxbuH9zg/W0JMTOdTTAJfcJpWhmM1locVm62oyhzs7eNjwmjNwfEBmwUcHsxx1tK3HcpoUiz0wUKgCBFyiAR//X0FpK1hXtOmDaqCqlb0wyWawK1jh9EGpxTOau6eHOBSz6c//wlOK+7eucuT559ydnrGSQB345hPnnyMJjNYLa0NIUCWmqfeaNpuzWze0EyOOTg4Jvmef/GDm9y4fcLcRAyRw8ND1utL6srS/9lf00wcjT6hC5YPPvqAYdNzf++IP/r8Q1xT8aMfvYupLMOwwjlLwnNyMmc6m7BdbamaitmsgT6StET0k1zqFVma40NIKOtoXEUMF9RNjassL69JZBr6lj/4f/13/PDeQ54MazbLl2Atg1FUpW5qiOy5GXmAkDqOT25xY36H/fk+KsPvnRxxcjJH9Utmew2GTN18i60P/Plf/y3f+cFDXp223L63x88/eo+5seybis9ePOPmzWNObuwTUiQmyZ6gDCcnh/S9J9U1k8MpjVVsoijhSD6u9OCNADcJwE1JkZNm0tSQInVlqKuaYdsLU28EuFGx3WzYm88IXt57B3DTCHDTrmf1Omu7afngvQ9Zb7Y8fPsdbO0gZ2Gy5oQzmuMbx9jKFfUbidCcMaVkcdUsbrWQoZSRyMs4w9PnL3j85BWushwe7AkwT/D45WlJuYOrHdaoHdNapLEkKospSsanKNCMyju2MGvHKC6kyBAiJmdOVi+44VcMzW3O5ods1y2/8d1vYU0pUaHE9hYma4q99BinROlVR3oqxzDul683k75SmSG2OGdZ+R4dMihNn6WwqIpNunNyhx8e/TarP/gEzltC3zPETLaGzaMXbFZvc+uH96h15KOff8pP3/+Y58sz2piw1qGsZRUG4qQiZbDzCUYrooq74nxQHl0LKpofzQljq7AyOG1p+x5rK2rnQDmGlFHKkNDEBDEM+OixxrB3eEBOgU3nS7ogQgiilxcDVd3w7LNHfP7oMSf3bhOL3l8GQo6EKMXja1Og25a//vP/QLvuuHPrBvfu3+Xj9z/g5fOXPHzrbZ68esHBzDBoCFqXhzOhidyczKFb4eyc+7cfsmePwEsqtK7nzJs58z3FbGZo1wvquuHk6IDz8wsutz3/7o//gN/57d/mMGyxJhOqjI4a3Th8jgztgDEOW4r52sOTp09omgrSAu0MgztiUk+KIsxI5DbkUifJSlIHPkikV0+nuJHQ03tC5YXKHaXm0nc9lpr1xZJsrl9cB9E6bGOPMQ5TIvY+iNyVHstiDobY8cnH75NT4mKxYlpVLM9fsmk3PHryghezGe2zj5k4RV0bOg8GkefSKqH0gMkek9Z86+bvULcz0lnEt5a4WLNqa+y39jk8ntK2K7quxWmH7geWm8R//8f/lrqZ8k//0W/z6tmHvPQXuLnBNRWvFhdoLVHBdDKR2oo2LBcLumGgqTKrRtPZfWbzE2H0ZWHHaQwUUkHKcm477/GDZ7Y3x9rr7e8wdCzDij97/gH9EDic1RgdXwO4kHOk788Jw5b7977Lw70H+Kctm/NHxBBZ7b1g9fAWt969ia4zYXtJ3w106xa1DfyH//ATPvj0E+7ducuP3r3Htj1loyyTI0dLz0ePPyk1QE1tbQGWluVqgakqLtdB2JTVEQd7RyhEUsxah1F2p/uYUyb6wKbbknPm4OSEqjJcLpfEGDFRdF1DCERgOp2zWqz45Gc/5Ts/+B5HhUFxBXA9xr5ZNef11XYdf/Knf05VT1huI81sSo6JdrNmu15C9Ny5e48f/PiH7B3sCbVfgdXCftRaMyqgaC1gzepRSTRydrHgJz//lKOjI6lp+YEUE48++YSoRIDANRVGKYZB9nes58vnzJA1+8e32Cwvyb5DWjMsSksdVPKTRliPMVC3FxzlFjO5zWqxYL1Z8d3v3OFgOmFs2o7B78Tlc5Za/cgnKFnJv1+lEGdqbh19d9fXodVrDBfAuopKKX7r4XdZ/odPUa86dIzEoRNdxqAIL3ouP7XkA8fBvuHP/uyviFXN/YdvY88ucFXNdNpw4/hbWDcKbmrQ4wMqTiurvAv1d4KdQGTsZHttlY7/nTJAZfHGoBKEMEDo0SQIkRgCykiUMKa8ctE5yyozhEKNHxmOSYgi6esc4H7L49OPyQpOP3/MTx/9pRTRp44Pz34GSuN7yYFHYJuk1J6JLBbP2G9m/Ivv/BPypz3LRx8QtgMhJ/K0pn77Jif/4CFHt2oYOs5PFzz6/AWPPn/K5y/PWSyW/OyD9/nWW3Oe+nO8VjB3nPenLJ+dkaOkLazWxFj6sOpEy8CzrRZkanom9Qxtamo3pWkmOwUXiagTfduyaTfM5zNu3buHUol1KxFyKqmOmAJJwcHBMR/8zd/w+POf8w//6T/5WhGayhoVLDpKZTorWMZeWg00pKDxXqKZ7fZc2gxQLHzm2UePpSZiDV2/wShLN4D1oxxShhyBgEZzphX/83/wL3AfD2w/fk5c9/gQiUZzeTxl8eNvcfPXHjCtOjbLDT9572M+e/SUdYh4n8i0vLw8JUwSn3anpJnDq4GL9lUhWmnasECNEl4mohtNrw0+KnLqGRbnGFvuQz1lLL/HXNQxYmTbt2SVme7tlTrtm6+UE8FGck5UlWUdBnSQ9NOQkjhPJWSAezcf8P35b7D6dx/DRUcYehFdtobtk5dsNm9z6wcCcH/2/se898EnvFxdMADWObSzrKInNTUJhW0sVgshxWiDwpB0xBqHQrF/tE9QhRyFodKOvvdYV0lqECuSW9qQMKTkCTEQoqeylr2DfVIKbFphNKeYyHgBuCng6obzjz/l8ZMn3H5wt6Tqvghwvw7ZJsdEd7FgsGu6xYrJnvQp5jzqOCoef/6Ely9PefjwAW+98xbWGuqmLmohEpGN+riSMlSlXiatFX2MPH11zsvT86JsElG+sEG1pvMRW6TUlE7iJItUXSQzqWrqquI8BlTp36Pc7xjkedJGSSN0THxoZzxhzg/MlL7fYlRmsexJ2ZJSxhpFCp7KSVvWxfkZn376ObO9OXvzOYcHB1R1s6tRftV6IyusjaGZzkgxyL8p45ylqRzdeo3vOg7391mHwH8KG/oJNCrS6MALDUlbGuV5WA3ofs20bziYTeldRdsNzGZTphOh+a63G6q6wliLVgrrrNSzgkerJN/XjqQUs/k+09keXbvBuApj7K6B1BpLjIHzc1EkF3ZPoN90hKSYz6YQPCBKD8QoWrsp0TQN3nup4xT6bE5QuBjCyhoCi8slXdOLE7zGsrbi9q3vQpaDobK+agsYWUyAKfShXJpYtba4HPmtb/8I/uaS+NkFdgj4viMnBZeKVb/Gu0RUb6HCln/9b/+YrQ/c+s4DtsbiJjXHN29ycOM2xkgUi9HSsE0pIisDKopzKNT1ciIALaKt2mKsKTKqct26POQxRLaFUqwQ8d2cMnEQIxFjEKFqJemMrBXBD3TDcH1a+W5vLbePb5fPoUVmyxQ1FgT6iJErcm4lXZOyMERFkBayulJpkT4hRVICkqyTAvdbN29xfF7R/u0TbBdJoScN0vAa+g2XVSJOLbfePuKP//DPeHyx5M47D1n1HUHJlIX9/VvM9h8Ke0wbtLlikyllpXcnJxTmNYFw2CmgKr0TeiYJWUgVepr0tmmefWZJMeLsVZ/Qmy5nau4evkMeNQSL9JXIRsl9NlVFoxS/9fB7XP7RJ+izHhUjse/EuQZFeFkA7n7F/hz+4i/+ltw03H/rIfZUyBrT6YQbx/exThW1FkVWudzDLwJcpQuRooDthLpiHyrpkcopCSOQQr9zFq81KkJIAzn0copfy9JQHNQO4GpVAG4gZZlAAQXglqbt6y6lNLqZg8qsLs8IURrjnbaoUm/yKTH0Le//ZMX+3j7WDlTVBOMqNMIens72CH2HdTW2Ujx79AmNm6KrRtJ4KRNG4UcUum7Iot6922cRQE67PVZADbx1+w45RAyQbUPWEausSG+lIqmsDVFFlIooHKFIuUUyJiceny+ZhEwXM8kP1HHguHFgYHG+5HK54XyxZbX6kK7d8nu/+zscndyQ5vyvWG8WoVU1D7/zA5wV4xVzwlY1zjmRQooBvV2wuVhz5gOXKA6cxtrE0xiwKXFgIdSadmjZbjLzyYx50Jj9I4aTA5JSuKpiuj+nqWusMeVAZinAlgA1BHGqIXpp8uwDKTmUz/SrNdH3ooKdI5rCyrxYFCZaJA6BNAyYeYWyFVVVsd10wlqieKxK0hEiBqpK06YgpVEsM8RMjJ18fU1mk1aaSjWSg8+STmqaCZfLBUIal8kFEYnSTOkfUTZwMN+HbeCzly+wWmNrEWTdFuNt2pZucYY+32NuPN22pT7YJ4bMya0bor4yqUkBFDJ+RMVE4Gq0h+y+FoFZrWlmczSKnAJJS5SWfCCGgDNO0gUpCbpWWsZZoEtvS2bYrLDWChEqRoL3xBCxzpKCB5V2UlIhjabieivFyOpyiTKGyWTO/YfvoOtKNB1TZrlYcHB4BFkmSeQUyUl0O0OK7O0fsrg8p+u6otgQSmuKYjKpyN4ThgFlDPvTOT9971O2dkDPYN5HXrko7RQ5czO1xO6S6dLhtGY2nTBEIXncu3+XrBQhimyZNoaxumVKE/LY3E25I7aqOT65yXa9QjuDNjIWJ6eIsRVGa9abDVVTY4qsljRXa6xxZD9c26FVkymzoxvS0P0awLWVo3GWbrUm9B2zg0OWfuAv0pahANxae15oRdKWqfI8rD1mWDMdKg5mU4aqousGZvMps9mMCAJwG7EHWmucs8SoaEPAqIxxFq2kD3W2f0AzmdF3G0xVYfQVwDXGEoPn/PyCg6OjIgYd6NYCcPf3C8BVorJBjCQv43om0wbfD1cAF13EkousYoZhCCwuFgyz6wMxsS0Obaa4WaSazLETRy4ElFQkr0ThJ/If/ugP2Fw8Jw8RU6BNUJq9w0O26wXJ1ezPZgyblh//+Ie4+QEpiKxd0tIrStG2dMZRVxWVsaIyYi1ohUVGKU1nc+7eukkz9Dx/9ohRbyzHRDISv/W74RGJMFLvSeLstMaHgRAsz1ctN+dzhrZl00YuHn/Ksw8/YDqbkoee9WbNphtQ2lI3NZf/5t+DVpxfXHzl3r2RQ9uslvzJv/mXgvhK70NIGWMd1hkao/lf/PY/wjwf+EdhQt/2uK0mxjk/TCLLo3VFfQFN5WmXLRfPTvns/U+pbt8g3jkkxoRx0qNEAQ9Wy5iJFALVpBGCR5GEEbapqAkYbaSMxhWVdSexktn1VKCQ4m0KJK0wk6k0IUvzkdR+cqQLXvLBCo5Pjnnw8C329+Y7KaKEou89zpWU5jUPcFU1vPOD38DVDmUc2jqsc4RB6O0pycylFCPNdAYhsFosiL7l5nTKi1XPn9SGlYJjDTEPvNIWrOOWi/xoT1HHLRMyJwf7BGXA1ZiJZu9QgzHUk5rpdEpdVVhrmcznUvTOGWcrlCkNmkYAR0qZ4HuUtoRBpKpC8KQUaddrzl+9wk1q+sETek+77UgxMZ3NsFrAEUacoA0WFQN7B/v0XU8q6jI78eiv49GUKjJLhr7r+fzjj1DGCIVeG2KMqDjgKodzE2w1pW4a6skEU1W4quHeO9+V4vv4elmcy2Q6oV2v8d6j2yWqafgkRB5bhdVwG/jED2AabPb89r5B00vqdTqhD6BNTTjcExaaMdTzKbPZtIA5izKaqqrpBplSkUtze86JWAR1m14AVQqJodvK2Y4BHyPbdctmI38fQpB0VtsWNlnNKLr8piunxO27D0RY2LrXAG5D5YRAoWJAtQvWr5ZcFIB76DTaJJ7HiM2JWClipWn7LVsVmU+m6GjQBycMJ/vkHcDdo65cAbgFTPrwJYDr8eUcLttAiloECNoNMRRHlMXgd5sty4uLQhWPhD6Q/IBRE2mRqGs2sSV4j0HKDznWxVCrwnwfAe4VpTzGTBe7a6dyx71V3SUxb7l3+ybN3h7r7QoQIluuasIQyX2H71qqZoLzYqeS9zhXcefOHV5dnHIw30dPpsQQuXX7NjkFHj99ystNL6o2tWVSNRwdHvP22+/w4K23RBw9gaobUDLyy7ct1q+hnqJNzcV2xWp9ycS3KCUkEp0GamOZ5Ah+A1nx8Ys1B7M5b92+wZ42NC7yYF7x2Wcv+OBiy6P33sP7lr6NTExi1hgmJmMmDft1zWK9Zv/oSGxPHoXMv3q98Ty0YZACPuy6EUgx4vtMzJr1p0+Zbgz7HtJgdmUGj4x8SNajNlv6FxuePXvM44uXnE0Te1Wgf/GUHCL3336L1ofdPDCKuKarnAi+kiBdiW0mpE9tPOgKqdu83l+RMyW9FaFEe0CZHKAJwRf9MYOtHNlL93yKQhSZzGf82q//mL5rr1TiyThrqJqKajIp4ppvvjabNX/2h/9W6LbWoLWhqmucq0TYdWcwQFlLM51QVzUzW3MwmzN8csGDdUsbM8euYhsc88FTETncnzFtgcuWtUqYaOC8o/nOXYbbh0Qv91OpTBsS624gxZbh8UtiCCJ/lblC4TnKA1f6WLQ1UgMr6gFaiVhyipnzFy/K/ie67VYYgSiytSjndvJOfhiIMYoMk5LIpJlOqJoa9zVqk8Au2lJaagchBqlPamRIj9Ks2jUjK+wqzapKw68pU7mVqPUXpfOIiFRPJjVWa37trYe4dcf3t4p7rcdmgwuGW2Ei4sGuYX+lqReJmDdsLzteffgIV88wP2rogheDeHZOjgJipFQd6NuWetJIH9KuDWX09ElaYI157bpfH+8hQ1cz7LILIUg/GlX1Wgfsm63tZs2f/bt/Je8zSiiNANc5jNVMjOF/+bv/GP3C7wButdXEuEdfAK6yFfV5ZuIC28sN509f8dkHn1Lfvkm4dSBRVeVEO7OYA3HsgRwiVdPI12oUSH4d4Jb0a0nfwpVwUs7iOETSSRRUJN2tMdOZ9EApRDWmaFR2ZSRNBk5u3uStdx6yN58LuJAYhK4fqFwWQH7NlZJnWD9HaXj66WdlzqTYAe1q1DBBG0dlLE0jFHw13SNZjS4DhpbDGjuviSaTVEswgUXwzPpA22/QKlOrChMdjXH83m/+mEhm8fJzqsrSrTp6ZTDALEA/dTw7fUlMmT4OxLYlbDcQemFVBgdEJnrGXr2HcjVKZX7/xw85vnHE3cM9am25decmZ2fPyO0Wu+zoVmfcnh3wtF/y6uKc46lj5iZ8vLhkOml48PYDbC1jxYyVDFJTfTWR6c0dmvdUVUVVObq+x6civwKoEHjy/od8/8H3UCaT8VAaa3udSBNDCJH28xes+g2L1NHOHc3xHiFnNpdLhmHA1DVuNt3l4p2xpS4wjlMXVo8ufRYJTTbjFGtdDqH0njHGTkkK2dJwqPDe07cdl+cXhGKsfIjoypV6mdQXYoy7FKOEf6KRKHPEAGXQxmFMtTOKb7pyBj94Igntpd9DbV6bb1yMjojisquj7ZuKb//OP+VwofiNvE/sA7SZxJ5QRlQiRINbeiq74dWLp7z/wU958uqC5tH7bPLAwf4Be0eHBC0pRq01ztrx00LRe8za7AxGyiK5ZbSWAa1c3RNRLx/ptlcGo+972T5rqKdzcowoo0WXzlVEBtJIDCHz8J23OTmZU1U1X0eDJeVM3w9y37UoqChtigoIgJybrMRQasr4Hl0+Vw4isru7D2MzqUTyqzJH761UcVTd4HZw3BwyKYgY1EmyhJzwKaO3nmq14ezFYz7//DP+9snnTI6O4T8+ZbNa8d3vv0tPKjJccibRCpUV/VZ6oFSRRFOMwq9KZNJMKKBCeNCj7p7MEJN7kcsZCilirMFVzbVVxWSydunLem1fctk/32dy1qw+ecJkq9kfRoCbyREaFCFHkg+w2dI+X/P06WMeX77kcq7ZaxLd6XOIiXsPH9D6uNP2U0it01YiTzWKXv8iwBXnlgqi/eUAV2pj0QvAlQkfiugHmeqhDdZVYssUpMJmns5n/PBHP2IYut1cxYzYqnpiqJrJ9TYWkaTau3FQwJ2w3WQqdVHyUKBUQuvw2gR7UaoRj6/K9Gm9Axu1cnJOcmDuFFhJ3dZWEWLLZx/+hE3bcnmx5OTwkO997zt8+uF7fPjBR3z/4bd5tlpgVUe2SnqPtS3lnMR+1bBXw7pdc+vW99mrbjCppiSfqA9m7N/Yo3aevX1H6ltcXfHOt9/h0R/9MUcHh/zxf/opb7/9HW4eZ8ywpm4sfhmx0xpTW2ISCbR6ZDv+Cjv7xg6t7z0+RNpW9BIxpqTFAl3veblqueP2qaYNeR0JbccQI36i6YaO1cUFbb+h1YGzSeRysMSF1C6ef/YZKoOtK6aFCKG1pqUrJAiJXlRxbLqMRMi59FiUpr+s0u5wjwy5XB4GU/osttvNbkildaLCENfbkhC35KzRqTROZnbDPSU4k5EdI1r2MVLFdG2zm8kMRUF8V7gGQrlvxogOoQzGvNJAC13H6UcfM1czUgplmrgi9p7eQDKJHA3dixWbxxteXJzST2pOfu17GGuwy5U06laOFArVltLrYUobxBi5jBFvvkLkGUVORVkAUYJXpQKfizp/KsX0rh+IITL0A0O4lKjeB5RzaCPNnznFncEwRjOdzr6mankxvLEQORJSzNcizsquZ6eQXVQogyfz6KILsUBiIWM0dVURc5Ime1WmDcTE808+4cHbU5ROKBXIKRCGyJAjoRKU31+saF9uuexWnKmB/e88xLoKv21BKc4uLqjn8x2Ly1p71ehaDLQU3UUPLyklTE2ACMroclBVaZjOwjbNY+o242Omb3sskdNXr36lcvnfta/94FEK6rrCOfslgJvR3vPk/Q9591vfQ9lMYoAi8dXpRJ4Ygu/YfrYSgJs7+r2Kaq9hSIn1+SVD8Oiqws4mcr94HeCOpBCxAyPAjX8XwB1ThHkUK4fBD3Rtx8Xp2a5+HKIAXKWKpFP6IsAdZxWmsY4EhZTi0Pr6mYUYAxcXz0r5I199Vq1LE7UpxBiNUgaVLNZUuLqR0UPOCb1da2latqY8o3DWRsn06EwKkS55YMtPP7qQNhoyp+vHfPj0bwV87DneO/8ZGU1lNA6Nz5khZbTO5Ozp2sRZCPyT3/ifcbyesvnwMZtlSwiJPHVU9084+c23OL4/Q/drttuOx58/Z3m65P2fPeLzZ09ZXC75zd98h01cctkvqQ4dq3TJzx8tiyC9whWh8K7ffuXevdn4mJTot2uh65uyqZTQHWFivULx5ONPuHvnPrpSDGpgmwe2W89qdUnvBzoVWavE+dCyiVmmrdoyGqGp2a43ZGevJFyK8zLalnlkkpYyTu8aC9U4F8yMsi95N9BTIwMJswJfpFzazRpXV9y4dROFNEu221bETnWRW8kynHB8LYozE3HiXGppQvdPMV27wC7iqP0umtlFeqpEolqm1PaDJyvpNSFnNoPnyc8+5fvf/j6xyuRNIHVS+xuUIlpYn76ibdesGbioAttJTWg3xK7jxUefCvMPjZlPd8jeqNKIiSl7a0pbhMRtWWm0iWVKbjGiqiR0do2r4hZ08Qhd2+P7gefPnnHv7bepmwl9WAnJQQu9mgwhvj5PrZyvr1NDA2RSdWG8XSWdJBVXmjelXptfS9tJ8XVkRyqlhL2WSv00C5qPRGLwnC1bXvGIvb0j4jqShh4/eHorvYPryyXb9YJt6FjP4KJJDJsMasvpJ58R2p7tcs3td7+zM5ZqeO3+qxHMlRaVAuRkHl4obEwRrR01+CSsLJFZAXLBR4auwxOph76kUK+xpaNDA7yXadmppD6FICICsy+XHbcLwGUdCW3PkAKhMnR9y/Lygrbb0prA2SRw2Ttpqs2R548+R2WFaxomUsAUgJs7EZreyTxZoaibLwHc1xiR4zRxAbZFuFmNVHbFdrsWwkWWGn5TN4TVRmbMaSevWdLXVwCX1+xf2tmGEOO1gQKAcw13bv4AlMwr1KZMxShgXk5v3hFXpPQvMwRHxRKrE1mJnVKIo81FdPuKwl9SsRlQSWzr7oOJ8xzPolaGrNjJxBURKpQ22JT49v0H3F4dsfmrT9BbD0NHioBWrJeXDAyE/A7TWeKP//DPefLqnOmdY+ZacTMMHB4dYiZHHB0cFqau2Sn+y1NryEr6KJ37w6/cuzdyaEopqkp6PUbt95xzaezTRCKXLvJ4u2H4+COsh9YPLGNPrzNDDnir6CvFpfa0SlIF0sic2T8+AmuonIyNUKUmkwtZQ0JvqRGMQwNJGe1GtCYpFdFZLNNbkZuQlRYkpWSu2GTS4PfnbLqOzcuznZBuThKx3Lz/Lb77/Xe5deceXedRSepyoocoSt1jbw++SF+96cktK+dMGAb5jCUfMs69UsDQlt4SbUB5fErEFLAp83LVc/zJZxwen+BNwvsWrzJDzly+uqDdbOiyZ1slTulZL1ustkVCLKJMZrlaUJceE6WLzI5SaGN3NGiFwrgy5DKzAxACavIORJQk6a7+qZE02XazwlWWGzdvCp1fCbssDoOkLlMiB4r48ziocZwr9TU8WsrEvisovSBoNabsyoBMROLMCEd+V4eS+13ePeXXgJzekQJyFkbsRVI8ffSIh3fB1I6oAn3q6VEsTy/ZbDb0ybPVkbPes0hB6giVJYSAmzZ0Q8dmsRB2aml5UAqpnY3pUgXayDBWNabetblSVIdCXKCkHMfhnnL9/eCJMXDn7i0Rm77m1uaUGNo1lLMy1vBEjOM1gKtGgHsPXSl6NbBNA5v1IAA3eAG4OnI+dGxHgGsU2lpcXdGuN2RrfgHgai0jYZS5Op9fBrjG6LF4eAVws0y0/gLA3W6omoqTGzdRWbFZr+m2LSkEspY0KgoZE/U6wC02I6tCCskJHxIpfD1tVwVYnbFkaittJT7lkuYrGZLydSYRcxgn6EhUZ6QkkEpmazLbY3ZwSDLSthCCELK0MaiUScnLs5tEWCIrxaSZstlukFpBxuQsADhnGWaLONJJ5bgzvcHj//QhJiS0EwLSVkmaPm8i9uyUfLrHLaa8ev4KM51ijOboxjHGVtS1w5oaO/bRATmO0wQkW5QzxOAZJ3T/svWGcbECIyQBozIxR0gyODGnjMISneHFnmfRXqC6jrb3eC0jJjCaaC29s/TGYowVP2VcoSMraZK2hmo6IXoRtUwq79KNWptSrFegrZAZyUivlNzoESmqiNwgsjRmF3SjAGsMD+/d4sWT56BF447osc7y+//0n3HnWw/kgcnQttJMTZQhlTkk4jiGZPDE1OOMuXZ6TKEwxZmNslwjm44ESQai7ZxGLg4l5sRzG9h7+Yx+vcUmzbrbsIw9m9DT+Z5BJboKLvXAJvX4ViKVlIV4oawhD4F+s5XDU+o2WmtMGe4nk7QVZHFg2hp0KuhNi/FNZYCnQRUeSCqOSSyms5bZwT5aG5bnl4QYGHphRWYyqjLcvneXBw/fEcOTC3AohuO6K1MUMnLRuyuvFUsaA0TJxFhJ26hCsc/FmTHWJQrWgKJ6XlJQRmuySqxM4AkR9dmnTFXF0A0s+patinRxwKtE72DtEpf0MhYjRWIYmEynYDWNqQjDIGNOVEHTRqZAqyQRgDIKkwwESQsrbSQdnNlR+kXdfwSDJSVWQIbRShqqK8fi7AJ/zeGpI7gV4/vVAPfCRR5vNvQff4z1mXYYWCWpqQ854q2iqxSXOtBpSaVGgfbsHx2irBVG7JgGLvVOtERhrzs4Wxig2owAV5V9KQDXIENAgaxfA7goJpMJIe6xaVvWL16hjS6SVglbV9x66y7f/f673Lx1h3Y7CMBNVwBX5v7Jv6O+63VXzpkYEnHI9NbS+16icSUMUa2kJ3GcEJ5LmhylRVW/aD/6IAQopTN0PVQtVVXTVBXGaAKW29+6j3OuEM8qjBPwlJRm0kzZbha71gxfmNbOVTKa6+yMEAYOnWNtFH9sMhcNTHViXwUekcmuZornNw81Jm/ptpmbxwesQiZjmDQVk7t74ngrSzOZUNc11lqqSYM1lm7wOFvJ9VlDNZl+5d69cYSmnRX4nBLO2F0emZywWR7SYarwdw/ozhPbszXSl2eZ703IU02nzC6FskunGCtOSBemnzKYpiZrrorfxuwGSSqlroZPqiySL2oMk6Ek0EUpHTm4FFSeJdlN8Inv/ehHxBj55Gcf0i4vufP2Wxzfur2rAeWirpBCJIeI90L/VcqK1mDbcXn5nGG7Jl5XHUApdFVJMixljJEHKStVsnni1HNhGFotpI1IYk3i865j8WKB6hPbIFFAVJCtZnCartastCKbCoukD4zWVMzQxqKdxVQCVLTRu9SFKfdXlFhUQUuUr3V5sKTGY4zIQEktIaPNGBmIE6mmGTuruby4pCs1o1REj7/zgx/y7Xe/z/7hITkrlotVQZ+/etz6f+6ZNc4xjsBQyHHV1uxSmnpEhSXKAUkvWSN9PqmQQHRhKUUiOSaMk6gkZk1WhlezSL+9oF4PdL2nzZFgZL9CbRkqxdYZsm5k8KISKSbG1KG1mNqVtFGRGjN6dy+kLHIVGYvC0dV9AGFejvJAOWcwGc1VT1saPG9979ucvnpF3w2FMXmtjSWrUuP7CoCrR4C777l8eQFdR9cPeA28BnC7yjIYi9G29Fm6Mv6InT2ophPCFwCulCR+EeCWHPdXAFyZgvyLANdpzcO7t3j59DnaWHEG0eMqxz/+Z/+cm3fv79J529wLwE3j5GuJ8smZ0A/43ot48DVXzhnXNLiqwdUNlVE8f/qM+cEhfbuRe6mz1HxL6nXn0IxlTPfnYg+V0oShY33uhcg9ZgCU4uzV05JlGe2CzHIzBUjUTVOIYk76RIHOOYamYbp/RG00R5WhfXbB0brDhMRBVUHUnAw9dhPYbyomXpGWHW0Ekytm6476xg3St+/hg0iU2Up8S4plzt+6Z+g2aGdR2RPDJTF4IZh9xXpDUkgi9gNWG5mqK/j3anR3LqPplSJbhzk8gBxR2pL6gWZPs1QGqxuiyigtUZqMFrcY6wTxW4st6Z8yCkeMJGOEksthVruG0yyWqTzoBammMo7eiCEG0IhIsYqJ0EcWl0sevPOQ0HtefJ45OZIJyaMhzVkx+AE/9IS+ZX25YH5wTIUl9D2r83Munz3Fz+b4X7HRv3IpQYy5pOlk5tGouKFK0yOgpKFSK6mRuGzILnFxCJe5ozu7xPteWhqMxRgHE8fWOjCizYZSZc+F7aeKakbVNPgwNozmqyL0zrAoMMVI5ASq1L60GIycEIMPu2hyN38JsHXNwfEhR8c3uDg/5/LsnOh7bty9w49+/Teo6onUumIix1KPiHE3f+66S9IU0i5grDhyMWRSU1CFGJLVeN1lqKGWeV/KOlSZPyUppoTGoSshk+SccKWNwzeG81sZbwe2ZyshGCmDdTXNnmZtpH9Sa7eLYrSxUhszUv8d2zYS4zhXClgYlUDYsTSlhkGprRXjLdRbeQZyLsw4dmQm7RwpwVvvfBvehif/8U+uubNK0LxS45CqXwC4CmESXgHc+EWAuz8lTzS9MlIHKw5KaSOpMH0FcJWSqd2vA9yr93sN4CK10F8OcGWcz1cB3BgS3/vxjwkh7ADu/W+/zcGNGxT/JfYnJlEMCeEK4GIhRHzbsVq+pN9cbxI4SNbn/PPHGFtx/3vf5eXLlwyrFeMrRhToUEBYsYnikggMBWxQznPpxdVGVF10ETAu6elUaq5aCWCLiKhBKTEWecPxuZZti2MaXmUs8L/5vX/G/GXkt9QBcRjIbSbnOTHPSToLi/wyMmk8i1ev+Oz9D3jv5x9THx/Q/6kIhB/fPCEUsGyUltSuQgC+kxppLin34L+6af3NHJropRRUWdBryoVtqEmA04roA4FMNopm/4Czly+xOfOqdbjZVGotpQ6mjcbWFQeHh+SksNaSSDTNBIMoMI9KC9F7MqKsoLWWQ5WF8BFjQCuomgrrLLpQXpU2DH7AuUrQXXGGYrQMMQWef/6Ei5cvuVwsuBkCw7Yj9D1h8IQYaYeBzWZDt1rz7NOPePnyDOsmrC8uefn0CckHLoeF5HevsXLK+G2H1mPRWmoFuqikKGSa8Zj1yiCkjfEhcw6OD8FputNTUpbprzdPai6zBlMDUhMzI1O0KAGgRFbMaIO2FRhdancZO6aSR5CgRqq4uTIYjLUe9YVJ3uNnkVqVSEV1m45b9+7x4Nvf5uP3PmBx9op3f/gjMLZMxpXenxACOfmCdlu+Xs4xEwaRNotBEK0pqbqdI0mZEEuqN+edkaBEbXqUU6Iol+sxjRd3hjHmwqqra8zJMSEOWG3Zth139htinVEU4o02ojuo9E6NQZUeRFuMdNoxeHMpH5f91RINC+lD6sQ79hsS6Y2qGALkruqbutTcok907cC33nlIM2mueWYTvuvRWv9ygDumdl8HuAeHqFIeSIOn2VMs+AqAa93uz9aZXVYiv2bAza6O9CWAqwrANSOwugK4aZcSRZ6JnYBuwg+Ry4sFb73zkNANPP88cXR0AyjjsQQj0Pue4AdC17JeXDI/OMFVFt/3rM7PuHjxlH46u/aRVUpx/uoVoFi3a/y2xShFPfTSDF+UmlQhaiglANQoqZlJG4pEYKNDUiYVrQlRAdoN7YxytrMqkWtpqxibU2IxOiPbdjzv40+okHn5s59zr7klg5hDKKILgagyQSewhm7RsVw+4/npC85zz94P32Eym+KHgfViSTOdMBQewphxyOOzOt7PkWn9K9abaTlqg7GamAIkdYWiKdTSBDpHqiAKEybDECL9ekM2Cls1mAQYpPCbMzlFyeFqI84RKfYaLQPhhGUYJdTtW+q6lty2FsN7MJkwrRtJE3QdmzAQy4gDOcADRhv6vsdUDZP5jO16UxAvWFejnOLk/rc4unePrDSnp2c8+ugjzp5/zo1bt7j/3R+y3XbElKkne6hswFmq+Zy7736P2PekmNk8/vRNtnO3cowMbTsGAbiqIicBDFVVSYO1GmsLeefkcqkHpCiNnblpmNy+zXa7hRDY5gRmgsGQTC6GwmIrR132TJeaWVM3KMB7L5ELYx1Mxr4YY4oSiEQwIYzXJkYnp1y0G+U6rbHCoCs/S0HfFxcX4jRypttsRDknBGJKGG0IPrLZrkT9/OKcy9MX0sx/zZVzIvjhSpLLRzwZrSWtoox+TbJM7RwwlIJ0Sgx9L4oYTYNRMul3/B2tDTmLcU0xElMiapie3GC9XGJqx9J7TDVFFx1MVZhmyhr2Dw4KQBDjVFUOZ5ykXZKM04g+SHSlC+ArWoEpS6N4zImmEnUZhdo5Sh9CYf5KlC2zpTLWVYTgOXvxaicwcI2dxfcddd3sAG4ssmE7gJt/EeDW870rgLutcbPqFwCua2oODg7ISaLAlDNN0wjAjXGnoRn9QCbvAG4uADdESQVqZBabKYCNfAVwK1dDicZfB7gpRZ5+9piLly9Zrlb03jNsW3wnLN2YIq33bNYCcJ9/+jEvXpwLwD0/5/T5M1KQzM+1l4LZwZHUCLWmPjiQNhojEyzGDAYq7ohCUYtgthCbdKH8I7UpKKxMtRMNz0iLEDGUaC3v3lzpMSZTu68rbbHW0PU9IVFISZkUAs8+fsStb++Ra8jbQPaBvh/obSZNLO16wfblktWwZV0nNnNDnyL94pIXH30qkn8xMbt5sus9tqZolZbWjFFgWSNyhF+13pAUIt55RNMhJlIo6hs5oXPi1/sFkyHiq5owdPyhnTOfZpyCpNKuoG52KEMxn06xxjDEQVAQSZg4UeadpZQwyojkVRSVEFE7SKzo2PTDLr2hnMNHybVrjDjEEmLnLOks5xzb7VbywuN47yAjYJy1dCFycuc+J/OKZvuKtutxrqJbb3HTKS+fP+X+975Ps3eIc4btasX28vwq9fqGS2mFqytBmUZEfP0ggqSmzAcajehYdB/HmOeidi0TuDO9D6zOzjFkojnBTYS2rFEYLQe3bmrmsxkplbYEDZWrUAmaqiEbGPqOYeixtui5ZZjYmtqK0dRG44dB0glOIo5QyCwEMNYJaUFpmkYO5ojWl4s1ylXceefbLDZblDrnsw8/ZHF+ysmdO8wOTzh7+QpS4uLVJcN1U7myu5DBh6JbWNCr5E6iiOqacaaURMXGjhMcxHjocl5zTjKnjVxG5VBQLXL+QyCkiCrAbHOxQBPxtmI+sWDKwMXyLCklbNsUxJhmVXrPgMrV6Cxz9/p2K4opSgyU0pqpc8zrWu5Nyqy7LXGMpMsASqVHByAp5eg9TksmRbtK0qnXrPUopZlMpijNDuCmHMkxEhF2m86gU6CKItNlsqIPQkDKRmGbyVcCXPM6wDX6CuCaEeBmur6jrmthcu4A7pRZXaN2ANeXeXCBFCEhALfrO0zdMJnN2a5XmFJPM64CV3PjWw84vn9/B3A///BDLl485uadO9x55122W+nDrSZzjLKo2lEf7HN38i5xGEgxc/H+31x7b01RcdmlFUt7y9iDpsYIvhxxiZ5UGe0iApNqjNS0IiqFqObLe6QyESHnDIkdwJf3yOyOdUkJDXq8FsnqRD9IU3qMnG41Lz76hBu37hJMwvctPkWCMawWp6wXC7rQ09rIK+W53CpUb8Eotlsho63XK5jUpR46ZonULkpXpcfY2DE78svXm7Mcs4SrMUaUNWhrMKXwn3PgYx94+eIxD24eURuL03B8Q7Ec9qGaY5yDghp1Ye9NJjO01ficiFrEgMc0jw+e4CPOWbQTpQFTiuHkTFKGupmQUxKJmAymEtUPo/UuQvY+oGIQZXcEAWij2ZYiqypsuK4bpD6hHVNnOdmf8UnXgTElLNbcvHefiyfPmB4dMZAZ1msuT1/gmvoNj+7VMrbkiZNkw52rJC+uKPU8UTeJ3pd5bKBz4t3YMWRNyIolilUIMpdLK1QWYDAabEHvmflsLmSTnEUnUyHz5lJEaYUfPEZbUhCKvzTtKlHwrkVNA+R3UZphiAwEmTFVUpUxJeqmoZlMWK/XhL6nbpoyPcGijBNFjqy5WK5wkwkTp3BBpMVcmR5u6uulxL6wUpam44Ja9RghjSg2ZjJlFFFVUndJFCYUUnSHkkXL0lwbvYhip5wxOXIz9vyW73lPN9xOPX+qJ2iTmOrAQEWKQaLC8npaQV1VTOqGjd+gKcSaArxiGgSqBoUz5fezJSO9UkPObLUm970gdq2LLFMozcQy7RgUCagqYYht1huEodiIEsbfmcT56iVGR+8AboyiJxkLUFA58Q/6BbaPUFe0Q8e/t3vsTWVY5QgMfhHgzrBaMygvrMb8ZYAbMcqKOHAsAyBDT0pRAG7Xy3OzA7j+FwEuhW5fWHtfBrgyhV4AbvCRG3cfcHNe0XTnbLsBV1WsLxZU0ykvnz3l3vfeFYBrDdvlku3i8vr7Spk5BuicoRDUSBlVRCNUCWXU+G+Z7CyjrtTulVRpYVBaoZMiAFf+QFLExrir3rIiGhFTLHXXkoYcnWs5L6K6JA30r0zmydlLYudpbM02bln0LZvtwLbbMORIZ2FlApexo2+z1Nt1iaDrSpq81+uSOhbnrLUmGal/U3gQLtpfKQL/xkoh45yfrJQ4stLnkX3E9wN7deC334afDT0fmxOmzZqYDNnOMQU5gbDMRLvQMp3t0fte0KmS0Q+iZ2gYhgGtJXqZ1xOGwVO5iqgijasltaB10V4rpIIsN3IYPLbUFJq6IQYxQqHMqKppaOqa5WqFLX0bOSeGENFWs3UzPh4mhL4nW4OtK5LOxJCp9+Zcnr0gtT0+RQ7v3eHyg5++yXa+tq+U6dumqIKYQtnPQKHEpwhlTLkuApkmZw67NZ+cLfndkxmfDz0v3D53bkHrZ+DszniPaiM7inLwdMMgo2ByJmWDDz1ESR8qY4hJRmeopCAKOUacrcMYvZMiikr6UWLKGGNERUNrNqsVfdeVKQWKruvk52IoT5UM9YsxoFzD9+4e4oY1H2/bnROZHR1cnz067q9WY3JBVkzixFQS8kGhaEOS9J4VVqEe65alSVY0P4M83HWFKzqXikhuNT95eUnXJPadR7uaW0eanCyVOUA5i7ZFwbzoQVauwtU1euhkxp7KMpampElzlvuWiPgYqIowbwiBgMLWjfRgOYkkrTaEJMMoKRRyH72kes/PS4lNY6uKdrsttbZrphxLDWpXK0sJZa0AXArATYGfDZ6XL57w8NYRxjqczpzcUFwOh6hqJgzUcuYF4IpCTNbgyUSNAFxjUCm+BnAztrISdBu1G1uUtcZ9AeAqTKUKwJXsRybjQ0Sl+KsBbop0YcAoTdaWaeU4dDOWQ4cyhmbSMFSaG/fuCcA9FIDbr1ecv3h6zdMKlFrW2KITsrSxiOwZKCMRfFNX+BAY+qGkpEdykN5FcCNZSBUnrhQkLU5SzvR4Lu2OOEfKmDQyrbliWhcHmFPCKakBRxKtijx2A9uXj6i6xDYENni8FtKJrwxdpViZRNS2aFNK1DWvJ0JMcw7tHKa0DImsrtjDHQtZqQKivxqEvVmEVogK0hJRGnBRhU0Y8TFhUstR3HBo9zEms990PFvtU8/3hGkzomUUqXjjZDShSxjtsLUT8ocaR12UfO3YIKkoTBwxqFkbUk7UzYSu68GKFFddOZqqKk2EkhatqprUDziriSozLBe4qmFS12y7lqg1k8kENQR8CPQxUDuHsfLabbfFOMvB4SHbzQZTOamtOEfbD9dm4ymAlIrKgtQhxl6oqxlrJc1QCTJVKeO7LX+dMylu+f9sHHHvhJnd4JRjcIfousFaJ1FEGbthrGU222PdrjHSTYwzBmerXU9NzmCtY+/gkBSjpHk0TPIUpTSucsQQcXVNHATFxpSpagtFFigmmWCbcyJ6Lymq2Yy27QQUJRkAWbuamDXeDzzPE2q3hyGzDQOmcrhJVfqQrrcyWViiqjRplzOrraB1YdIpGW+PKsQnTcyeHK8enJFZJ1wRaebFKlSCOCTWqefkIOKHDf9an5Cc4qiOvNocoJsJ1rmCcgWsWWuZ7x+gjcW5ilD2yxTtQFC7Zu+qnjAMA9ZYksrMnUiVGWtKk7+It8YojOKYEpUxxOLMdEllbttWattaM5k0XF5eXvvM5vLMpzSyBhQ65y8C3K7naBL5vW/D+/3Ap/aYWb1miAbcFD0CXCWqKwJwHZPpnG5ovwhwlaaqmx3ANVqXfRGAm1SidtUO4PosvGjS6wB3EIALNHVN9AM+BJG3MxqVG+q6YrVa78bUkBJ9iGir2No5Sz8hdgPZWmxTEz2EkGn25lyeC8ANOXLjrfu8+NNrH1qJLktGRSUNWkCmKem4MHSs+rYQsrSkXBFApK9IiQLIRtJMUf0xJVW5c3hG7Uggo0SgMK0lGMhalQxckd4rtfecEiZrsjFc7gdWscX7BUPflikIBqUtunJsa0fSDqOrnR/RO8GAwrSeNLv+vR3DspC3hPyiyEWh6qvWGwuOjQQmkUaTnG0MgZyijAVRmifrilB79tySrYdcHxKNxSJF2LHB0xiLsRWT6Uwmxg6DEELcOHoh4JyhaqY46yAnohepIWMq+QDWEr3HBy+EkSisyOBjuYliRIIPdEnqIRiFVRaaTBcHHA7nHMMwsF6vqatGpG+CZ9NuQZtCotC0bUvXtkyaCfuTA7bbltV6LYj+mvWIMZWVytgPXUabCGmjHDQlqHdkFfrgCX3P7x9mfrQP/66teE8pbk47ni+mmGmNNpaMKvupyUaor1lLD5bVDltVlEFlaOMkrVNZsAaHodt2ch1GUVcN/TAUrUdDyBlbVQTvUSrT9x2TZoJOoIwmDEEeMq3pw0A465kfHjIoRT+kkrLrqaoGlyL9EOl9pHKGWT2hbVu23fArEdl/zuYmRUGpI8K1KCs9NWSRY9JIWk4h0XHykaCEMm+dY1SpSKRivBUpC/ut9wN7JH5nvuWCff5lq9mfdKxbjZ0eoKuKnMpDrJCmXgXKOYYhkBGNSArZAYqkqDGikGEtqkxKt1aUSmztCH7YpeB05YiDsEutkUGr1k6u5KkGT13V9H5gu14xsT2z2ZTrpxzzVZ1RUdiVAhZiysQU8DGj05b9sGHPHmBsZq/peLY+oJ7vgyrZAP0lgKs1IeYCcCuhgo8ANyPnWV8B3JFoMwLcnIUl3XV9Ye0mmtrBFwBuoqonpL5Hvw5wa8natF2LMYZJ06CGwOA9KULlHMY0AnBDj3WOg8MDtpsNh5XDGot1lvbr1H1zyQpoIdZonUrQJmxuynilsU1JLEhhk4rQq5z1oqCC1iQtBCNpzDZghEwi7HEpYYzzHsf6mVJqF3yowirdOROF1PPIMtFbW+LJAamxrJ8/gyzKHjePG3oHUVUoRIzcagEq2toCaERvUmtL3SiyGSN/KV/sKCpK7c7KV603d2iUQxfLwAQtfV0BcNWESX+JMQqbBg7mhk/XR1jjiKEnxlzy5bWkc7QWb28tISbabUfOUvsRRpIiJul4l2GduaQLpAPe2cQoj+W7nuQEicg4DU3XdaULXsRMQwj0g5deLq2Z2IYwpkxi2uk2tu2WGCN100gxPivWy6WMkZlOSFGmDqxWS4w17O3vE7zn2k2qiHL5GAWkDMpqMIlSPpPorTCWQhCtvKw159uOn609w1Qzq7YyMWB6gp3MUaUPL0ZVasoGVzeljqmxrioRHIUtlbBW1O9V0XuzzpdeHU2MkaZpiH4QenBJLTaTRlCj8kXs2Zb6hWXwHm0Me80B/vwVq4tXmGaOc24HAPquk5lXsxlD17FqW7TSZTab+Zp9aGIwTS2zv7J0lgpICIEcPJWVMwiZGKW3CIQgkAty3anAKHHWqbAaUwjyoOvM52vNOvdMp5HGbDnXh9h6WpRUIjHmnfqHthXT2Z6M6MmSirTGiGSSVlgr98dVtaDymOi6ViIik7FOyCMxBTnfGZppI1MbyjiflOR+hnK2YgjsTeeEvqNbX+7IUtdbEmmm0sf1iwA3YY00LD/dVKQCcDdeQXVA1EaEGLJQ6Q2l/9RVNNMpIXr8MAizupK2EwG4lqqevRb9y/yzykgUPwLcEDx1U8vooBTwQ5S0+whwh4EuxR3ANRjUpKFLfgdw+74nhEBTT5g0E7wfWLfbYngbtPeiQ9lumU6mTJoJm3bLcr0WAH7dM8uXMuRZeAXEMhan1EUZbcPYa1bso5BBiixbqc2GGEmDZEXG9gg0ZRKD9NZJtkKemV2bU4oYa2mc1GBT0WoVGbErx0Op4aW6pr51m+A9afBEm/GqwumKqNKOaa2toXqNaa20oqrqIgotEze0llr2OOZHGL6/uvzwxg5NGTBOHmCjoaod3UY66g/3T/ir95/iXgRO7jaEUKNUTSZiMiULCzkOJCykMnk2B3LKxcBaximo1lXgPWTZiJQSVYnCckqkLLTqppmitaEf+iK/k7DGMJvNGAbPdtuK2oCtaFzNZrul32x59snPObp/m5vf/iF2u+Xl2SsO9/d3DrtvW0KUmWCTSY3Rls16TV/62vb29sk5s1ksdrXF66xc0ovaainQugqNLjRvSqNjJmkhZpBkEqwzikNlGVyFSyv2p4an632wDh96CrBDO7cDD8Y6XF3TTCZ0m61sdcwEkqQljZHoN6fCODKlzpAJfkuF9AeqEnmFYRDjWhQGQgh0fb9LE+tkGHzH4D3ToxOClwGe222H0jKqRltL17akTcRUjr3ZjK4bWK5Xpeh9/QhNaUPWluCF9SWtOGJwYzFoPmRUYYVpo0uz+dgfZshZeqxGId+cM77UOVKWlN++tVin0SFzWK94FWu03SMF0XMkJXRV7WpoOStpZh8G2m5LzooUM9EHqroq6g+aHDO978UZF0JKnxJDCDTNlDjIrLeR8VrVDV3XSU1Li/KJqSti1xNjYNNtmNYz9OxAqPVfY5pBTIqMiOemckaUGQGuoqqmNP0F2oBNPfszzWfrI8xrAFeyKLIvSl0BXB9iAbgasojSoiAmqSGmMj8uI4QvUFgnEYNG0Xc9lcu7Rl00dF1XyDEF4HpP7738noYJtQBcJWUUmQWY2W420hrR1FRGGL+r5YIETCcTYpARRct+ISWJ/f2r0TrXObMKUJpYJOB2DeMllxi1RD8qFzUYEiqPfWLsZhUKDpTJ6yX5Xlo6RLhYWIQGW6ZfUwIBZWTPwjCglIyzoQCkVAg6IpGHBB4pQ0yELJMIjDGcPn2GVRDijMm+Ffk2daU2JKWbA1JpzcoqU1c1KgnLMSpkgku7FSUja5H8lDC/v2q9sfTVdH+fyWxCGAY2iwW+G3Dako0hhIGLNrLYwsZPmPYTcgSdPTl66kYomJiEMhltFfXEMQwyQTcVZel20+GjZ2411poytkGx6Tqpu1hLjBFX1Ww2W9r1lmY2pakbtNIslkuW3ZLZbEYzabB2gveBzUYmBUxnM7Zk4mzO+aZnv2+ppzVv779NRrFZrVhcXIBWTOspOWW267Ww8oxhPp8Rh8hyIVIs2hj2jw6+luGVsTCjwZRRFykrkhLD64eeqqmpmoZh22HrCXvNjEefPeOoTbgjSGlCtoelvigHQpkS4ZTicN1M6L3HDxGlpH7U+x4TIpPpdJe28H2Hj6GgcHDaEAm0Xcu0nghrzGiIkW0r9Q7nKkn19B1tmYpcu4qqqoi9Z/Pxpxy+8xbu5JjlYsFiuRDmZghUVU1lK7rtlsVmi3EV8+lcnMbXMLpKKUxVSw9OjCTfk5PUO62SKcs5lLSOLorlY404FdII0vAdSeIMY2B+eEi/acFq9iaHXGxg+aJnf15TNTX9Zg/K1OJxlEtKUSSgS1uAcYbVqsdZGWTq40CInpqaup6SyIQ44AdfEK1ECcoohuCx3tNMZ/ggkXE/eIYQmE6npCSR/Jg6m04m+MHjY2Lx+eckv+Vbv/v7OFddf2+F742pFDoKU9ZVlj4JwD06OOYvfvII9zJy454meAG4EDBZlThDhKFTGdrrnCUm6SezzhVjW+S1rKMfPCnHwqSNAnBDLCIPMvKpbqYooxn6AVNSlc4aptMpg/d0WzmvomsoNmToOp58/HNO3rrLjXe+j9lseXV+ytHBgTxPIdJtJXNjq4rJZILWms1qwxAGqqpmb2+flBLrywXh74gkftXKmZ0Y8m4MVsnOpBhRRSqq+CBhbCJRWfGGpYk6vwbEim0qrOaYouxrlDDPGottXOnXk7rzyLTWWgacqpLBiF4EJyT1nriZA/MQuVDCkXiFIkWPsaoEbxlh++uRI8mkabBaSFaa0m+mi36tkihfoYheQG4KGe0kS/T3VkOLMXD+/CWmqnHGEkNCO02OkUpbzhcbtp0nKUUwMzZpUjZEk3XNJo1DKy1WO5RXHLoZ5IqcWkKUPp9qMsUVcdsheVIINJMph3NJ7Q1hEKMcE7PZjJgC2ljatgVgNp8xm0ohfbsRNpc2khps25bNdosPgf2TE46Oj4ghsFlvME5SHs6Jcsny4pL1alOcp2O2N2foBtbLhTQCK83ewQFaWRanr67NxssZUsjE6KGkUJWz2MpSzxom84bYt/hui0qBZqrAag72HH/+Nx5/EXjnoEKHGpMDNntUzhhD6V9xKJUKww1i6sR4hoA2imkzF6knJO3b1LUotZRx9kNp5J3N5zIbLGfarcyo2z84lKxDSvR9T9tJb9DefA8fPMMwiNrKtuXpiyfsp54H3/0+PgbqSc3R0TGXZ+esFgtxbE3NfH+fvm1p10tBl1+jhEYhexgtslBDlOhMK2ET6uJ0UpZmbxVTAWGglQWrMHVF01TMDuYYBauLM1TyTJ0CU1HVcLlK/HyROUDx1jARMkPsUcnjqqJ8bkSKSluLqRUx9Yg+Qy4GXS445IDNCt976qYh6ETwQQxUSjg3ARVpu46262gmjYi3asvi8gLvA81kglKwt7fHdrNhtVrhnCOTOetaNusF+tGj66fJlULXDfW0oZk2hKFns1ySO2n5wBgG33PRJlZb6MKUZpgKIk+enMIvB7jT1wGuZAzazRafPPP5HOs0KoGPme0IcJ0lRoVzNevNhu16y2Q+o2kkzbxcLFn2HfP5nLpMQfc+sFmt0Voxnc+kfjnf43I7cDD0NLMJbx++Q86wXq1YXVygtZG+t5jYrFfScrADuIHl5aUQcazl4PjoaxzaMRpTpZ5V2htK5j1rytQRichScWyj7ueutzDL7LwM8r1yxnNIAtzKMFPIZCORb9a5qNeYMkmgRP9ZyhcZBdZK315OaBR3t2vy+YK7+3Mav+Z/cMfcOtHkpAnW7diVxlyN95o0DdaJZiY6CUM6ackGxUIGLDqdQ2GAhxTKDMu/rz60nAndFq2lQVKjZQOcY3J0xObZM5SCpnYkDCRh3Ix1i11OOEWyV5hsaOoGUAw+0Pc9Smtm0xkpBozR+K1nGDwpbeUhdZbKGXo/0Pc9KUbme3O01sxmM9bLJavLS+q6xjhL1Uiz3vnpOcvlkqZpaJqayXRKt91yeXYhOXyrsdbR5zXb1UZSBhpcPaGa1IRh4PTlSyFmOMd0OsVqzWqxIHRbQSxfo8CeYhDGpo8YNJnIkHuGDF0vtRrvhUyjkiGhWCwv6XpFSIot++ShYYgiKpCVpnJWmFJYjHbgoZ7sYVRN8ktJy1Q1VV0x6mjlnOjbVijYzorSQwhs24682TKZTEhkpnsz2vWWi7MzXCUanJN6wtB1bFZrlNHMplNM01AhKO3w9l3uPXyL/RH1ohi8Z+/4iHra0G+2bJZrLl6dgoJ6UtNo97X8Wc6Z0LdkPwgzsCBUVSrfOYpTk/SNIH2jDYMXY+B9mXi9taxXLdYZQi+sN5XEcKz7nrPTFUlpsp2yCDN8qRdnDEM02KzJuUheeUNdWZp6n41qWawvqZsps9kM10wwWrHZbujbLcoo9vb2JLoaelb9ivOLS/b29pjNp6A0Q9+zWW+o6oqjk2OCF6e9XW+IiFNTTUNOmXazZn50xOHNE27euX3tM5tiZHV+ymbpMK7eDV/UpYWgMo6LxZa29ySt8HpKSg3jaJNsJmwTu/NpdYXyCuvm5GzJuZX0YoSqmWBTLaN8UiTFQN1MOSg1yD4M9D4QUst8PheAqzVt16FQzPfnTKMwIrfrjdgiY9g72Ge7bdlstoQQObhxg6OTI/wwsFqusM5ii1LP3sEBq4tL1su1sEhrRzObM7Q968VlYY8a9vcOUNlw+erV9Q+tglHrM/SDRKdNdfX90g82DhrVRpquJfkIxEhK4/S/XMo1kVIsL/Jvtkw5kWhQK2EtKmOkP08eHnJOeB93DF+ltWQYqqL96Ht+mg2+1L2rvWOcSxzM4Kw7om6k9zgXpuooOzffO5D+1xhIKKra4awwIGMQ8Ka1YTqfE0LAGisp7fpKs/OXrTdyaMZojg4bcg4o7Yh5kLqYN5w/25J9oLYG7wx1rTFmYGTgWCO1MW0Ku0zJBNq6EgX2+d4+k9mcymiWlwtWyyWurjk6OWYyk8nF68WCxeUlk+mE2d4cqy1aKdbLNV27oapr9g8OmMxnOOtYLpecnZ9hrWG+N8doh9Ga1WrJ+dmZoKvZrBQbk6TA2p6UQtl4DSmyOl/KoL+cqffnVFVD6HoulkuZyGwU+8fHkh695hK5uUCOiiEGVN9JfccawmSGUpK7j04expNbN3nx6DGZiHaGAQc4jM1oq0kYAkKu0RjIBpUVVTVhvd4w3d+jns2x2rBeLxn6nvnenKOTE2IIpBDZXC5IOVNPJ8yslYJtCPRDRxUC8/l8V//brjecXi6Y7c05unFM3/W0fcd2K5Jes9ke9x68BTHz6OOP6fqRCDInJ+i2G4Z+IKaMq5y0BpT60teaWl3moaUoUSuF+ZnKFGuVMmEQpI2SFhGy1NNIiZgjySOpnMmEFGqRfSsMsP3jG/iuI4RIXVuyFgdGTqLyoqT+FpGIUKLAjHM1g4/ElGmmc6xzeO8JYcAYQ1VV2NJXtFosSi3UMpnNGApZwfsBbS3TyZTaVfR9R79tGbwHrTm8ccJ2s2Gz2eBDQGtFXdfMpzPazZoXnz/eEWDefGWylxSp1oo+6iIgq9GuYnJ4yPrpBq2UtM9giF8AuFevE3MkDx7jDHXVoND0g6dtO1CK+WxGjAJGtpsNQy/1t8l0gq4stdP0w0DXtoQQ2Nvfw1hL5SpWiwXLdktdNzjnqAuB6fzsjOXikmYyoWlqptMp243h/NUZGSHd5ODo1xs2640I4mqFaybUzjL0PacvXqKQGvVsNsMoxfLyktC1BeB+jZVBWcj6kvYycDR/SNKKTNHPzdI/+oV0Ys6QBPyS5bxkJXJ0o/IGxqCskxR6EpkqlTO4jLGGHCMhhF0dTY0SdhSmNUWhpDieoev4wSzzT78PfztU/FGnOZxsWW0tupqgnCsDgYUTkEvbinEV3nsURgAx0i5grcP7hK2kBl/pihQ7rK1BS51N/32lHFPKdH1hCyVRBojBg4oy9rw04mHLxZZoShtVBF8pqhRGGumso55UHKgDLl694HKxwFnH0ckRt+7dxSjNdr3i9OVLYsoc3zzhWw/fQinNarVmcX5JCD2T+YyTGzcxSmSAzl6+wntPM5lw6+ZtYcnEzNnpKd73aGs5Pj4S0kWInD57Tu+9GIzphMo5UghsN2variMD9WwqGnspsTg9k4bgksPfOzzE9zIr6DpLKS3jY7KE+HVdy5TdJGSZHHoSUmRWCdT/t73zDrCrKvf2s9Zup8+Zlkx6BRIg9C4CiopdFOu9yicg2BBFBQVRUFBQEBvqFbF79YJcRLkKCApEKdJbSEhPSDJJpp5+zm7r+2PtOSSQOkyYMNnPf5mc2WefPeus911v+b2GzcaNG2k06nqzEENCtjp85Tc8DNPSIceoDtd3Qwxbf8kb9YbeGFxPOwfprE7IChgcGMTzXJxkklQ226y+rNUquDUXJ5Egk83qcvV6TVfeBYpcS45kWudzSsWCLkwIQlpb21Chzu9UGy6hr1UbWlvbcBsNqoPamLpuA2EapDJZvTFXyloqa0g5YJioSBIMX9GoVKiHIYlshjDqfZFGpEpj6C+vir6woR/oHE4ygVQekpAw9HWoUk+IRPmCwY2eFr82BDg2tuNg4IKE0Nf6lEKCZZh4UdhIhBYJ26QRhW0t28KM2hwC1ycQAaGtIqFuBVJSr1SQrkSY0eRp18U0LdxqDb/ewLItpGFg2TZ2wmGwUGCgv79Zxp9M6nxkqVikrCqYhoEZ9VEOa81KSa41jRQ6rygNi0D5eo6d79LfXQE/wDYlviVxHIFhau1FoSKBc8Lm7LchBzfh2PT1F8jmWkils9iGpDAwSKlUxHYStHa0k8pktOzd4CDFQkGv4VwGyzAwhKRUKFKvVXEch1w+T8rMYJkWhWKBUn8vpmmQy2YxpA55losF+qvawc1mMxiGQRAEFAtF3Lp2cM1otJXyA4ql5x3cVC6LZTt4tTrFUqnp4ObbO4a9ZlEKAsXE2Z1kuhRrl6+n2FNCuI7Ooym0yILUXdYhChkEiGBI/cTXVY04SMd+fhhsVGGoRYl9reOI0hqgURW453lRqNIA08IwVFO1REhJAE3R+DAICBGU63VWVRsUrYCEE+IYdQbMdux0TrdxBKGuzpW6SEtaFqaToO662E5CV0/6PlGViS7hNyzdliAlZlQ4KDF08d1IGTQhDcxEVveEIJCmQElfVzGicGt1Uvmc7iWzE3p45FC5+ZCCuSAaBW7oeUpKsn7dOlrbWmlpa0eiKBcG6e3rRSHI5tuZvvdcPL9B4DboW78eL3AxbJtJkyfie3rzLgwM0HDLgCCbayOZSoLSxRylcokg0EPi2to6CcOQeqVGpVTE811CoKU1j2XZuA2XYn8/nqcbJB0nTTqTIfA8quViNFnZRxqSbFsegcStNaKZSztdNKrXbxji1bXBUqioYx4SCQvdcmNEDbNulAAOqXk1kpZBCfBViCMDTEthGDoBK0U09E9KhDRRZgJh2tgJG4oK07AIpUJ5PjWvhOf52LZNIpFABQq/5lKo1lCoKEybIvRCQt+nMDCAaUgsyyGdzlKr1yPx5gCltMPT1tJKpVyhUihovT+ijTXdQrlQpDRYiKSoQsyEiZN0qFVrNCoViMp7bcPCsu2XIKCr177veZQH+wkiSSQ7YSOTaZQQuIGexCtCH7/u6VlcYqhlJIBaFcPQ05AdS/cGBmGkSSoFXuhhCl3xWwnBwccSCtME05TNCkREgGVGPYGGTSabJplOUa8UGCwUQOncbyqrp0irMKTYP0CtViOZTpHOZnTPmVIM9vXTqNewHJtMOo1l6GKcQqlAcbCAaVkkkgl90jNtioODDAwWkIbESSVJWTamYWqHcJjCzypUVCsepqkV0QkiBzdwIwUJI9JYFAjLwfV8bNPCsgTGpg4u2sGVloVhWtgJh3w+R3/vBgqFIrZl09rWyvjsRAwhqZSK9PX0EChFW0dH08EtFksU+wuRg5uhs6MTKUxUENLXv7GZVxzfOV7flx/S39OD5+tTblt7mw6h+T6969bj+pGDm05hR60AtWqFRl03MzuZNKbU7SmbObiJBNmWFrzGcE++RO0UglJ5EVQ3kBkv8VyTSp8JwsBkqAmaZnguRBeOBGi9S9tJ6CZkaYA09fc9CHRPXxgS+D6m1AIDfjSiSUit4GQYJobtaKmwockOQ38vKfDCMCr31xW2rbZBtWFj0KDFCSm4DsLM4AW+bjGIVGSIRLORBk4ySagCapUqQhhASBDo1I+uRE1EvnhIaPi4rp7s4LrbFrDY6R1YhdEmKfSJDCkg1HFXaVp65pQxJGczNE9LRQnMoWo7ojLlkLUrlpO0DIJqlYbvE0qBk0gxY5+JGIZJYaBI78Ye6pVB7aF1jsNJOkgkA32DFAf7UCokk80xoWM6CEG90WCgf4CGq4tEWlryJJJpvIbHYH8vjUYV3wuRlklLa7suE/V1Urdeb4AISeVyZDI56tU69XIFz6vruUemSduELkI/oFGtavUBxyGVyzWP5sNBRf1blmXpKjskXmARQDTZQKBCC89tEKo6SInfaGClEiRzWWrKwFQ2FlprUUZhBhUoBAZGKLGE1qWr1WoYpmieTnzPQ4aKMKqSgwAMQcJw8Dw3CnEFWKZFEHpYtkPohTTqNXy3oU83UQ4t8EMq5TJupY4SUSWlsHAMSblQpF4q4rk+wjQworlg9UpFl2ZLQYjEtvTE2lKhgFurv7SaECFIJJPQmidw3ahsWIDnIixLyxoFYaQRGpWIC4EhTawoX2E5Sa1lKdBF4UIQKEP3WwmF7ymtnD+uHctO4Ulbj8QRQyN2VHMDUko7cZaVoHvtWkxDMK6rC6EUbr1GobeXwA9JptPk29vJKt1aUBocpF6vIUyDdCpLLpfFtEzKpQrlUq8ujnCS5PMtGIauAu7vGyD0dd9lMp3EMGyEgEJfH41GXT8fObynK4QgmckxpNqukBgK8BJNBzeo1Unnc1ErioMwdUNvKPVYk00dXKQJwkKEsGF9N/nWVvKtkYNbLNDX14MSkmy+nRn77Ivr1Qkazzu4pu0wafIkPE+fXJsOrogc3KR2cCvlEuVyWTu4lnZwgyCgXqpQKZciB1fQ0pbHMnUvWtPBDQOcZJpUKkPoudTKxSiCoqtQs7nIwa03eH6a3TBQCt/38F3JYLcDJgijjCFaEUqiCKE57FTnzXRPmFZQwrQQkZSUniahcBsuwneJ5LQxhJZ7C71wk0ISEe0c+neU0MUZgd6wCTwXYUicVAqv1kCYFqlUnmJ/EacRIBIhKcdiQ9CKiJwvPwj0YYbn84KmaaME1GoNAj/EMBWu7xJ6IYlUMurFDQk8FzeKEClEVC0pR86g6UoXHTJQQltUooFwoLAt3Uegx1t4yFAQRFY5FEOSV7qJ2QSEUBQL/dHRUsdq9QDFAfp71qOUIHA9DBVgWDaWaeFW6gxu7AEBqXSWCZMmEwqt8rBhXTflYgGBIpHJMGHSFKSQeK5Pz/oNVKslHSbIZGjvyhP6IbVKlVpJe3ZISb6tjWxLDhAUBwap1cqoQOvjZdpaSWUyeJ5LpVrGrTUIlA4vGagoFjAcFCJ0CTyfwJeYtqNlkUxL932IaAMI9cBIXQKuq+LsVksrhEdztOSQOgCRdhsiCvkaSGHi12qkEg627VCplBFC6g1fBAhp4fsSI1TUa4NgKGzb0soqpk3ohZQKg8hQV6RJx0YYFkIYNGpVSqWC7mtJaNFiU+jCm/LgYFOxRUlI5lJIaVIplQmDMKpA1PPaLMOmVqkQ+A2sIZWMYW66es3qdaudLVOH2EKtuDBU2SlEVCqmAmRUzuxF44fSuRwymgLMUFKcKHSC/nIZ0sNIZSKlflvnu6JGbaL+MRE1MSshdR/TQAHHNEgmk9TLVdzAw0kk6ZoyBWkYuI2QUrFMudiHbUmSqTRt4zowDJNapc5AXy++55JOp2lr78CMRL8LAwPUaxWkIUgkEyRSLUhMKsUiff3rtWK9pUfd24lEc7TMzjI0MkhPxR6aWbVlB9c0I0HybTq4el94bvlyHNvAr1RoBMHzDu6cSUhpMthfoGf9Buq1Ao6ToHXceJyEVqEY7BugONiPIiSbzdHeMR0lBPVGfXMHN99KIpGKHNwe3EYN7wUOru972sFtaCOQbmkhk85Sq9RpVCq4TQfXon3iBALPo16t4rkepuOQyA1/HppuXPZAlQn9AngSFaZQykP5kTBwqIsmMHROakh8GyLdyyGJKBVFeEw9HYVQ95+FKohK/yPJNBVNNnd9pK2NmbQkhimwHYdUNgmhj1+vIEWIrxTKMMhlHZZ0Kx7q9pkwSZD1HS0jp+pYSlf1ag89RChdom/agjB0CUIfN/AwfEkqkQZHO0fVWg3peaTTKd0oH4SUyyU8t0Emm91mCmKnDZoC/CDQh95Q/3solxZGEv+mZSKVJPR9QuVFm5KJDIfknMwoZushRIDE0LPUMBkaiRD6ejyBV63qMBQq+gIJHcc1DKyEQyqTRRg6b+A4DtlcjtD3ybfkcat1GrU6SimymSwt+ZamlEt/z0bKg0WU8kllMuTax+uZYFLSs2E9tWoVJxKgTbTkcJwE1XKZ7hXLGdI/syybTLYTy7Hxaw08d7hhBt2HIYTEtBMkMllCoRO0QFM3MwgjQd3I57ccBxVERjRUUUGDaMaYZdTkGoQhpgxxG3WWPfuMvndTD0JFao8pk8npjchr4DWqSKWVXyzbolQs4NdrGNLETibwAp90MoPX8KhVq0ipZ7gJQyKliW05lEtFSvUCqBAnaROEWnlDBIpKoRidDg2kbWHaJtlsC+VCiVqlTNJxUI6JEgInnY7yLcN8skI/X9OxGZrQoATYZoah0Rz62YNbq2rPM1Il0GtLN4vLqIpMoPCCEIVW45BSF34Y6PxqEPj6pBcGusRZapUDpNSN3GGIIaF3Y7cuBBK6IR0B1XKJcsHW+YNQoQKPhGFg2UlSqSzFvkEajRrJRJp8vpWAUE8zKJTo2dCDECF2IkVre7tuoDdsBvr6KBYHEICTSOAkU7rZPFAU+weGH3JUWrFHSKlbHXbAwdXFNNGA0i04uOBRKm7Nwe1GhVrhw1AhhmVjSotGscLg+g26ZzSdZeLkKXrQsG2xft06KsUiAkUym2XipCkIIXEbHj3r11OtliMHN0t7Vx7fD6iXq9TKmzq47WRzWZTSBR+1egUV+EhhkG1v1UU6rkutVsetu3pKggTrJfSkAqhQUOpzMIw2/HqI7xtYsopUSaQ11O4g0PkFLQUmogpCMdRPiS4eCRt1PTsuDLVhEc+PSxKRNJhSIaGvxZ1DD62cIvXIL8MI9ZyzIKBeVRhSIUOTUECtXqFY9qmGkqrI4tdTNHwRVU+GJBKWVjkJdURGBXouppCWzq/5AaEjdCN11JRtGJLQ06pOQ9Jljm1Tq4fUG942i8SGEXLUG2rQiFTSTam79v0AN6piFKS0vJLQo8pFpOyhoko9YVq6mi3SoQu9gFAE+J7b1DFUoY/vuTRqNR0nFvq9iTrkw1CPC6+pEMO0qVe0dE4Yhvi+x0DvRn1KsCyEAMu0MMwEpm0jDUEm10I6mcH1Glqn0EnS29evG8Atk0RrK6ECO6FjyRvXrCfwtAKGZdpg6qGYtpVgYN0GXLeKzggMY/GqMFJN0EogntvAD2paQ9CyaM57iCbuIoWWPDIsLQ0VBgTK14UpKjIu0tSeXJQ4DhSEgYtl6gXm+5GUmFJ41KiUBvA9n0apQuDW9Qkkcj5My8R0bBLJJOlcC5aVwLKdKNkb4Lm+LiJJpKiUy9S9ipbakyGu5+M4eYwgpFoqIwWk0kkta2RIsvk2KtUKg/39WIap5Yq8BkKY2I5NbbAQ9ecNj2aTaqi0wr6U2FEDuVY70INpA8/Dq9X1gErTJgyhXquiajWkaWoFd4EOSUaCpgpoBDVM08IP/KgpOCTwPZTnajFuy4rU74ekhaQeZ0KoR/MopR0XoXUi674eIunXGjSiXqdQ6RA0UquS2wmHZCaLnUjRqLs4CYdcvoV6tUoqkcCxEpTLZSpeEdM0ybe24gcelp3Aa7i6pDwMSKR0Qn5YzzUM8T0P00ls1cENpA5/v9DBDU29rmSoT+CbOrihCpAqcnCV/rl2cHUDvlut4lZf4OAq3dtnOzbJTBZp2FiRg5vJZlFBQD7XQr1S0+FApchmcuRbW6MNHfo2bqRSeN7BbWkfTyKRRCHo3bCeerXaHGibyGdx7ATVUonuFSu0gyvRDm5uHJZt4UU9scNdtCrwcEsOXs3D9xokkwmUBcLWw3yF/iNoR1YOtT+g5a5ChQhFJBjvEwYeppRNhZowjP5eSkXxSq2DaRoGKF3sEQQ+XkOX4gtT4jopHX0IFYEl8VHkW9uoFIu4noswJZ6wAQdpatUjQRJPaRUTlAFYCCWx7RSVcg0nmcS0HSzLoVIq6HxxMqmLzoIAoYQOA3seViIRVUSHI9dYHQYBjUoZ20lG6hMKr14HpRORjukgI7UPPfnEwLLsZq7BMHQyHV+HGkKhtcEMy4qa5UJCz23qs/meq78E0TRkMbQBhHr0iJBROFOFeiNCF1Xok4puUFbKByGpNyqIehWUiMbXE21Kkcci+xia/toIQkJcEo6DV2uAkLR2tFGrlKhWa9R9j/b2Cbi1Bv09G1AGzU1yODw/c0vPQ6uWylorLlL3CANdiILSfSJewwUVUg8bSMPAcZIYwsIPG4COvyvlYZq2PhUJqRuthVa1F0Loce1R1RNC6I3T9wkCF9/XkjeqoctShwyjZdsM9CZ0mNE0onlb+otRDAJKcjBSnlCYpkVbvgsr6eC6dRq1GlJCtVbGVgnaO8dTq9UpFYtIAlTgUqlXMW2bts7xVIolauWKXmfDjeQOrVtfryPDsPQEaLcROT/otVat0VQkN4wocqz0cxaChGXp9YYkaHgQBCip80hhw6UWahkvFSSwHIcQdHFEVF0qhaEHngqb0NcKJaEK8RouUgpCT4Ahda+NUoS+F4XBXCBSi4+Uz/0G+A0Tt17BMB2U0H8XrXzv66ZvaWgNyOiahumQSucIRYiZNrFMk0q5RBApwQwHFc3NUmGwiYPrIUyDwNPPKIiqGV/o4BpRn5QSWoNSvtDBDQJCFeB7DaRhPu/gug3cWrUpYKDU8w6uUj6BCKmXlXZwq4LqixxcgWnZCKF0I7rhYNg20hRkczkyqbQuEjEklp2gp7cfAg87cnAVAjvhIELBhue6Cf0GMnJwhSlIJlJYpk3/ug14jepLW7OB1l00nQSm4WA4Fsp2CJwEYb2iw+BKr0EVKBRaIH5IEUiFSgsHRDqgXr0R9ZBFguWGQgqFkELvAVG+GLSwwJA8mAh9LXkVuM1RQzLUBXDlao1ypayndSS1LqOKhBB814v0Y3V/XoiP5+p2CMfW6aPCYJFKpUoylSKXyZFIJBFSUBgsUKtWSCSTZHMtONF+P1gYoF6pbzKB5MXslEGTUhAGPvVqRZc4C6VPVUJofbYoyRiGIA3teUpDYtiOlv3xPQLlIRQ0ajVQ+sE5TkLPcTIkru/iN/S0ZhXtZKEKda4F3SukBBAGeI26fk3UaxEIXw+QjMYNaBk4hZIq8kx8hiYDh5HCvH4LrQ1H1EeDCgk9n1qk9wcy0isUCGFgGpJS30ak0mNHfKWQUs8HGhZC6BCMCpthxnq9iq8CEqSjGWKhnros9GlCCr0Qm3pu0kSYlj4Z+D7S1IvLdxsYphVt1roIREqJHwQoz8f0fSQQBB5uXSfadfuaNs66zHpIolcbL6FClBuiTEWghk5pumdIx+V1fk+g9fl0lbGBZZpkkmkM06I8WNCjPlAEQmLZKdo6cgipy65rlTLVqAp1Wwt4eyilv8xhEBAYAdL39GcTOgE+5CAJU6tbhCJKrquhAihBtVLEDpI4TgqJrvLyhzRG0U2qWi08Kt4xDAxhRS0KYdTpHhJ6+m+hDNHsdQojaS/leQg3OoW4DXy3gQoC7YwMafmpsDmpXA6tNaWdQCCSPNP5kIari1vC0EeEksE+nVRH6E1Qrx8D3x/m6VdBpVLE8ZORg6udRK9e1/kY08QxE3rNGZIw5HkHN9BVdYYR6tDs1hzc6LMFrocf+HiuqwUImg6u0awIBT0iZqccXFWF8osdXNCKG0MTFupBgFJ6QG0j0M5dW2cbtUqFWq2KG/i0d0ygXqlR3LgBDIGdGX4OTT/eoWnUOv8UKh9Z8zB9l4BoCn3kP2vZL6KS/vD54jQpCTyfQk8PytW9tblx41Cmia90da9ujvaidhU9jToMQxKmiSml1q/UEXEMw8YPfXTSJ6RWGyRhQM2Q1MIQ21QkLA8ZTcaWUrcRaX1PgbAyhMIgmUpSLtdIOEk9UUEKKqVBarU6pmmSzekUj+96DPb3U6/XcBIJkqkUJiM8PsYwTT0EMYrJDiXIQ9DH2qGKGaVzPwK0t+Y28NwGga/nfYnobxW6Pn6jrjdax2p6ykSNgCoSLAvDUG8OIjpcRyPTvYaLME2tRq90v5kUUe9CqCVXAqXnoRH4URm1Fv5EKD0RVugqGj0ZRH+5onePvowhnqdzK0N1QAEhyteiqUpo6aRgmPptSifI9ANRoZ76bDuEvku9FGA6Ce0tGRKvprX5DDuhvSupFzGRwrlhWQRKj2aRIsQyLZTvUnf16HlpmgjLgkAvunqtglvTpcgovYkEoa7406PfRfS8AkylNwi32YwbjVKJksuG0PJShmERKl9vHkpGHp7CbUQCqUoM6ZpGodAAFYT0rn0OIfScq2Q6QSafJwwVG8zh59BUEBK4DR22CgNkYOjiOiGjPiRdKWZEp2MhtIOgg7y6mMSyLULXo+6XtdMgAV/hu67OSRmmFrEWAhV42hBJPYDTixT9wyDANi0qgyWE0sbHTiSj068gCHxKVe3V62S+nkxNGGrlGCEQUn8e34scvkiKyFNgWdYm+VOBaCqxm2jpaf2ZwzCIilRAeVpSaVgILV/k+9rBxTB1xMZtRKOPLHw/QOqPgDSUHlMUObiB7zcdXEKl1WkUGJaF4zj4Yaj1GL2GLgzbkoMb7QGbOrigw8pKCULhR2LQ5iYOLmAoVPgCB3coL6MUWuDAIwCUNJ53cAthNAhWbObgGoak2LsBqbSepR8qxM5vrZthREZARWH9wNVVxXWlSOTb9aw4vc0yNPMviJwKhIz+30SpgEQmjfK0QQvDQId6bQs/CJu9s7q8X4sBOI6NaWhJw4Zr4YdRQZerCAOJ7w3lCqXezw1BKp/HVYLAt3BsLXghReTIBXq9mErPNjOi1hfPq9NwXUxpYJoG6VRaH3YqFer1Gm4QkMlkSTgOfhBSLVf12KZtOLhiZ0ZzCCF6gFUv6S81tpmmlOrc2V+Kn+t2GdZzhfjZ7gDxmt11xM9217DV57pTBi0mJiYmJmZ35SV0/8XExMTExOw+xAYtJiYmJmZMEBu0mJiYmJgxQWzQYmJiYmLGBLFBi4mJiYkZE8QGLSYmJiZmTBAbtJiYmJiYMUFs0GJiYmJixgSxQYuJiYmJGRPEBi0mJiYmZkwQG7SYmJiYmDFBbNBiYmJiYsYEsUGLiYmJiRkTxAYtJiYmJmZMEBu0mJiYmJgxQWzQYmJiYmLGBLFBi4mJiYkZE8QGLSYmJiZmTBAbtJiYmJiYMUFs0GJiYmJixgSxQYuJiYmJGRPEBi0mJiYmZkwQG7SYmJiYmDFBbNBiYmJiYsYEsUGLiYmJiRkTxAYtJiYmJmZMEBu0mJiYmJgxQWzQYmJiYmLGBLFBi4mJiYkZE8QGLSYmJiZmTBAbtJiYmJiYMUFs0GJiYmJixgSxQYuJiYmJGRPEBi0mJiYmZkwQG7SYmJiYmDFBbNBiYmJiYsYEsUGLiYmJiRkTxAYtJiYmJmZMEBu0mJiYmJgxgbkzLxZCqF11I2MFpZTY2d+Jn+v2Gc5zhfjZ7gjxmt1l9CqlOnf2l+Jnu322tmbjE1pMTEzMrmHVaN/AnkZs0GJiYmJixgQjZtBM08Q0dyqCGRMTExMTM2KMiEGbOnUiP7/u6/zql1cwa9bUkbhkTEzMKxjLMrGs2MGNeXl5yQYtk0lx6dc+Tfuy1bSvWMPnPnc6Qgwrfx+zgySTCd761tdw7LGHIWX8rEcLw5B84ANv5YorzmPu3FmjfTu7DbNmTeU3v/oWv/7Vt2IHN+Zl5SUZNNM0uOiiTzDd83nymt+S6Gzj6acWo1RcpLOrMAyDL5x/Jl85871856vn8OY3nzDat7TH8va3n8hnP/wuDqjVufKK88hm06N9S6NOS0uGyy49l9TjC2lbsYZzzjl1tG8pZg9ipwyalJKpUyew//57c9hh8zj11Hdy/FEH8egVP8Gv1UmO7+DhR57eVfe6xyOl4H3vezNvOeYQ7v3s5VSXrmKvvaaP9m3tkRx99MF8/uwP8eRVP6PvyWcJwnCPd+Qsy+SSS86ha2CQp3/yPyS7OnjiiUWjfVsxexA7FeSePXMKv772MlR/AZSiumY9K6/7A6VV67CyKbyEw+rV67Z5jUmTxtPZ2YZSijVr1tPfX9jjN4IdwTRNpk+fxKc+8l4ePO8Kqut7sSd3ccuV1432re0RmKZJKpVACMHEieM444x3s+76v/Dcnfdx0Gc+zD/vfYRyuTrat/myIYQgm03T3p6npSVLIuFw0EFzOebgffnXqecTej5OZzuPPfbMaN9qzB7EThm0ysq13PP+z9AY0EZIBSEohTANJr/mKGpArdZovr6lJcuMGZNZu3YDUup8w7ve9lqs/kGkY9NIp1iycg233/4vbrtt/mb5oHK5iu8HI/ZBd2eklMydO4tEwmn+bObMKbS1tbD33tPJt2RJp1NM7myjsXgFfU8tJjtlAq5t0d9f2O71h3KaseOwbbq6OjnggH2YMWNy82fZbJo5+8wkk0kxoS2PCkPSpkF9zXoeuuNeUIrWOTNZ/Je7t3ltwzDIZFIIAfW6S73e2Obrd3dmzpzCz665mKRtEfQOgFJUVq9j6Y9+R3ntBpzWHA3L5Lnnurd5nalTJzYd3NWr19HXNxiv05hhs1MGLfR9ahv7QICdy+K05ug8cC4zTzmJYOI4vvjl71IolAB9EvvB9y5iRkcrFddDCIHq3sjTX7qajY88jTAN8rOnkd97Bud/7D/4xMc+gGi4gEKaJvc/9gxXXnkdPT39u+Jz71bMnjWVX37nQtyefoa+ymG9weCi5biLVzKwaDnFMOTfq7up9fQRuh6JjlYK5SrlcmWzawkhUEohhGCffWZy6qknM3FCJ0EQcv8Dj/H44wtZuHA5lcqec5rYEY4++mAuv/QzJAYK9D2xCH/I4CgY/PPfKQ4WWbu6G79WJ2i4eKUKKgxJdLSSnNBJX99A81pCQC6XpdFwcV2POXNmctppp3DUQXNRQchAvcF99+u/xV13PYDn+ZvcieKVsJ9763t48PQvEroejUIJlEKFISiQlsXUNxxLJQg2M9xtbS3MnDmF557rxjRNPvjBd/C2N74auaEPI+Hg5jIsW7WWv946n7/97Z9I+XxGpFis4Pv+lm4lJqaJ2BlvaFZHq/p/hRLTTno1+597GjXguY193H77P7nzzvtYu3YDoL3Rc889jXcfvj93f+KrEB28vFKFoOG+6LpzP/wupGWx7l8PU+vpx85lOPhzZ/BQucr5X/jWSHzOl43hyAhNy6bVx6TE2yRkpVAQvuBvIwROa46Jxx7K3I9+gJ/f8g9+8pP/QSlFMpngzDPfy0EHzWXBgqW0tuZ4/bGHMXjfI6z86z2kxncw+bVHkZkxhYU9/dx3/2PNE2EQhNx22z0sWbL7ChvsSumrbDbNDb//DgO//TNL//c2Qm8bG6cQSNMg2dnGlNe/ipnvfD13L17JJZf8gGq1hmFITj31nXz4QydTKJYpl6vMmjKB/rseYNFv/4RXqtBx0Fw6DpzDxNcdw9PrNmIakiFPZvHSVfz4x797WR254TzbiUKojwr0fQuBk8+RaM/TefC+zHzXG6i15zn/gm/zSJRTnzZtItd8/8tMzmaoej5SCrxVa3nqx7+j94lFSNOkZeYU8nvPYL+zP0jFNBBRtEdEDu63rvzpK83BfUQpddjO/tIrQfpKCMG++87Gti2efHIRQRC+rO+/tTW7UwZtv31nq+suOQc5ro2vXXkd99//GKVSZbPQoGEYnHHGuznjHa/j8a//mO4HHnvxxvzCm5ASI+EgTQO3WAZgyuuOQb3vLZx51pdeER7rEMPdHD5mGiRaWwhcD7dYIj1xPEHDpd47QMvsacx462vITp9My76zeK5c5fobbuXGG29tPvszzngPZ735BFb8+U6sTApCRfe9j9L71LM0H6AQOC1ZTvz55fjVGusfeBylFNkpE0gdeSDnf+k73HffoyP6PEaKXWnQWltbuPnGH7Dksh/Rfd+jtM6ZiZ3L0PPYQpzWHB0HzmHVrfNxWrIceuHHyEybhOxoZcma9fzx5ju49dZ7qFbrAMydO4vfXHsZj1/8fdxSGSEEjcEihaWr9QlmE6a96TjmnPpOFv3mZup9g0jDYJ8PvoO12TQfOesiarX6cD7yTjOcZzurvVV9/c3Hs+T6vzDj7Scy95MfpBoErFy3kb/eOp+77nqADRt6AZ1//OIXz+LN+8zknnO+xpCH65UrW3Qe5p52CihF9/2PUdvYj5PPcvDnP8L9g0Uu/NLVL+3DvryMWYP2pjcdz1fPPxOpFD/41U386ld/fFnff2trdqdCjitWruHsb15LsVhm6dIte/MnnXQsZ73nTdx79tcYeHb5jt1cGJKe0EnQcLVBk4JZ7zqJmxcseUnGTEqxWdgim02TSCSa/65Wa80Q6WiSnTKBE778SVL7zCDY0MfdH/8Kx33vIhoDBZbddAdzz3wv/1r+HE89toAnfvm/LFq0fLNQzpFHHsiHP/BWnrvxNhZta2EpRWOwyL3nfwvlBwQNl0r3RoQhOfBTp3LCCUfstgZtVzIwUODHP72ecy/5FPMGiri5DGbCZuWPf4dhWRz8+TOYdNzhJMd3sKDe4LpvXUt3dw8bNvTheV7zOtOnT+Kb3/gcvXf/m57HFtAYKG7zfZ+74z42PPgkZjJBee16Hd5cuoqjfvlNEgnnZTNow8FuzbL/uacx/eTXEbbl+cLXf8RDDz1FuVwl3MRwm6bJJz/xn7zt8AN45NJraAyW2N6XetGv/ojh2AhDRy0aAwVW/uUuWt/62l39sWJ2gP3224svfPY0nrnyOnKzpvDa1xzFb37zp83+7qPFThm0CRPGcfLJr6NSqfHUU4sJQ306CIKQJ55YhOd5fPTM97Hwv36/w8YMIZj5jtdxyBfPorT8ORb//v/oOGguibmzuPV7v0QIgWkaCCFob89jGMYWL2PbFrNnT8M0TebN2xvHsenq6mDCuPbm96ctn8X2fP2FkpLeeoOPn/3VZqh0tOir1rj2ngd5/Hu/4pKvnM2rr76QRj7Hw6u7Sb79tfz2Hw/w059eT2ML4doDD5zDlZedy8of/Y5lN/9th96vsHQVwpCbnBgE6UnjqXf3jOCn2v0YWktb4o9/vINHHnmalpYsGzb0MWfOTL72pU9gAFf/4DfUanXcxxfy17/ezeDgi52g1tYWrr7qi6h/PcKD3//VtsOWEaHv4xbLqFA1Q47jjziAku9vZihfKi/83Eqpl1xwVfNDPnTGBSilKBTKrFy5Zouve/vbX8sH33w8//zExRSXP7dD11YqJDN1An6lhleuIgzJrHedxO9fYkuQlBLDeN7BzeUyJJPPO7jlcpXBwW07IXs6qVSSS75yNj03/JVVf/snJ/zwEn550992C2MGO2nQgp5+9lq8ktz0SZz0puOaP092tOKNa6fherTUGyy4494dvubEVx3K4Rd9gpoQtB2yH8cddRAIwbJlq/nQh04ml8swfcoEBNDZkiWsbtlrlVIQ9A/SGChS7x2gvGY96rluir0DuhoTKEqBlU4CAmmbzP3Ie5k2bdKoGzTHsZkzZyZz5sxkQ08/YWcbj//9fh588AmWLVtNo+GilMK2LUBvSJ7n4zg255/3EXr/9HeW/fFv2/V8h8hNn8xB536YVbfNZ+09D9Eyeyoth+7PLR/98g7fsxACyzIxDIOOjlakFEyePIHW1lzzNXPmzKSlJdv894MPPslf/nIX4XZC0LsCyzL5zGc+zKuPOWSHquiEEPQUy5TLFSZNGs8zzyylUCjR1dW52Wfq7y9QKlV43/veTGepyj0/+u8dMmYAiY5WDr/w4+RmTeG+L1xJclw7s951Er+7df5mLQCGYWy2Eb/wPtvb81iW2Xz+mUyKffed3axubWnJMn3KhObnrtTqfO3SH7Jo0Q46nVvAtky+/KVP8OySFZTLVZ5+eklzU/P9gMcee4YgCPjI6e9mwTW/2WFjhhTs9d43c9BnT6ewZCXLbrydzkP2w5w5hdu/8WOkFJimiRCCjo7WrToojuMwe/ZULMvaxMHtZHx7vll41daSxaw3UAqEFPQ0XD72yUtYt27jsJ/LSPFyVyYbhkFbWwup1PMGvqOjjQkTOpk8uYtJk8Zj2xZz9p7BxEyKu265C8O2SU7uYs2a9S/LPe4IO5VDm57LqE93tm32s9DzcQslslMnolB4xQql7fSiNd9cSsxkgsyUCbTOnYk0TULXw0g+X76OUhSWrSb0fLxylfpWytSFEEw64QjGH34AiY5W7HFtICRBOkm5Wmu+X3fvQLPUfcmSlfzsZ3/Y4slnuAwnHzGzLa8uO+lYAFpmTCE5rh2A9JQuVMKBdJK+Qrn5ei8IuPX2f5FOJ/mPk47l7//5Oep9gzv0Xm37zua4716E35ojJQXuQJH0xHHMv/8xrrzyOvL5HF1dHdi2zbx5e29VcDqbTTN9ygRMQ9KWcAhqdWSoqKxY0/wSeuUKhWWrAbCyaaa87y2c8h+f3W6v4pZ4qTm0KVO6uPn677P4h7+l76nFBO62/+ZmMkF+7+k675jL0jpX59Xsrs7mxi0tiz7f55lFyznu6IN54ktXs/buf+/QfSU6Wnn1ty+g9fB51GoNWlIJpGUxWCxxzTW/pVyuNp//lMld5LeiQiKA9pYMqlzVz3/lGlQYUlyxppmPRkF9oEAYVQnu9e438ZclK7j88p/o/x7Gs52adNTFxxxKclzbZmsWIDm+nWB8B64fkB4s8vfTL8Dbwaraya85imO//UUqSpHJpLEtE4Rg6dLVPPLIU+TzOaZMGKc/dzZNuJXrCinxN/bRGCxR6+mjsm4jKgyp9xeakQkhJXY2AwIM22Kf09/NmZ+7nIceempnH8fWGFYObdy4dnXJJZ/C9wOq1To9PX0sX/4cQRAyf/5DI54mmTNnJuefdyZ7z5iMUa01HWNDSCor1+BXa/Q++Syh71Nes57iijVU1m7Qa/i3V3HKh7/A+vW9W7x2Pp/jzW8+nnnz9kEpxZNPLuLhh59m3boNzbzzcBiRopDZs6eqa77zpc1vOJuGkl5U7voelt98B6v+es8OXc/OZxl3yH6sufvfSMNg0vFHsPGRBUx41SGYCQcnnyO/zwycfA67q2M73oqgnrD5xW//TKlU5tlnV+B5HoVCmWJxE2Pgebu0Imd4Bq1FXXriMQQNl4HFK1BhSOj61HsHCMOAZEcbRsJuvj4/ezqTTjhCG+j7HmX5H+/Y4feaeNzhzHrXG8jOnoaBLlMzbBvX8wiCAAmUlz1H6PuUVq2lupWFqpTCK1UQpoGVTmEkbMxEgvxe03TdOmBn0yQmdRGqEGmaLB8o8rFPXDysL+RLNWi2bXHeeWfyxhOPRqxaR61329VyhaWrqUel+INLVjIY5YwNe+jvoFChYvzh83DyOYKGy+q//WuLVbxbwkwmmHTCkbTP25tkZxteqYL1AqNVWrWO6voe/HqDwcUrUWrL69bOpGmdOwsrnWo+/+y0SajmmhGQTTFY0i0e1YbLxV/9AU8/vUR/kmE8270ndakLD5zD4NKVm/08dD0agyUyk8ejQoVbLFPZwQiIMCRmIkF60nha95mBMA1Cz8fcpD9ThYrC8tWoINT5ta2ECIUQTHnDqxh36P4kO9sw2/MgBF4yQXnICArB2g19DAxoB3fRouX8+td/fEEbxUtiWAbtgAP2Ubfccm3z35vue5de+kN+/vMbR+bugM7ONn79iytw//EAy/90J5XujToEHhFsoV9SmAb5vaYz72MfYHkqyTmfvpRqtY4QguOOO5yTTno1ixYtA+A9p7yRTt9nxU1/w0jYTDrhSOyuTpZs7OP3//MXHOf5fe3xxxdutTbjhYyIQZNSKNu2N/tZa6s+ppqmwQUXfIyWR57myWt+u0PXc/I5Xv2dC1nzjwcYd9g8JrzqEB646Dsc+LVPc9c/H6bRcHnmmSUUixWWLl213WbUSqXKhg19O/x5dgXD2RwmT+5SZ5/9ISZNGk9bLgNAW0sGsaGP6gvyWvX+QQpLVqHQJ9fSyrXUdrCU2cnnCIMAr1TBSDgYtkXgephJBxDYubQuv27Lkxzfvs1rGbbNzPe/hV7fp+H5LF66ijAMWbJkFf39g9GzgOXLV1Op6BNyX9/gsL3LkahylFIyfnwHhx8+b5uizslkgv333xspJel0koP22wu73tisStGQkuqqdQQNl8ZgkfUPPM7qv/1rh8K+QkraD9iH/meWEroe6QnjcMsVfQLMppGmSeucmVjpFO3z9kZsJW88RHbWFJ7pK9C9fiNLl66ir2+QSqXGsuh0DFCr1ZuRCaUUrvt8jm44z3b8+A71w6ixelPachlEtYZAO7jLbrydVbfN36FrOm0tdB60L2vuegDDtpj8mqNY/+ATTDr+CAzHJtGWJ7/XNJzWFszOthdVjW6GEJQNg5//+o+Uy1UWL16B5/kUi2VKped7Nz3P35X5n2EZtL33nq4uvfRcVqx4cV7ynnse5LYdfJ47wjHHHMI1l5zDrad8srkvgDZkRtLBTCRoDBSwsmkmv+ZIslMmMu6IA5DTJvHPfz/Ot771U/qi6NAhh+zHf119AT133o+Z1qHL3icWseLPf8ePTmPCNLCzaY654jza9tuL7nsfgVBhZVPY++/NZd+8lltv3f7nGxGDtr1y0nPOOZUTwnCHDVqqq4M33fxj5j/yNK865hCqzyzl6R//nkO//EmuuO4G/vCHW3f43nYXXso4+01zJe3teebN26eZN4tex777ziaTSZFMJnj98UfwyEXfYfXt/9yh98lMncCMt72WZ//7z3QdcSB7vf8tPPOzGzn0y5/E9QOMpENvuUrD81i0eCVBsO3CgSeffJZbbvkHQRCMpFe7RXZl2f52fp/W1tyLhIdbW1uYPLkLgDe84VgOa89zx4fO2/Ym+/xFOfxLH2fdPx/GyqY54JMfZMG117P3qSczYFu4DZf1Pf1s2NjHypVrtuuk1esu99778GYqPTvDcNesZZkvmqzR2pojkXCwLJMvf/lsUvc+woJrr9+hayba87z66gtZc/e/GX/EAYw7dH8evOQH7H/xp7jzrgdoNFwWLFhCuawd3O2lCiqVGr29A9t8zS5mWAZNSqkMQ74sSknt7Xl++bPLSS5bTXnNeiadeDTK87n74xez/0ffT372NB67+ufMetcb8A+ayyOPLuDJJ5/l3/9+gnXrNjTz4R0drVz97QuYWq0x/9OXEbrbLmpqnTMLw7HwylUKy1Y3C3/Ct76GD5/2he3m2UekbH8kEVIy7aTjWLG+l4sv/j7//fMrWP3TG6gPFFj9l7vp6uoYrVsbNYIgaBqR7u4eurdQdXjLLf8AdBHMD6+5hMROjI9x8jn2PeM9TD759bRPnUh59Tpy0ydRcWw+d9E3WbduA319gwRBGKsyRCil6O8vvEhibNWqdTz++EIA1q/v5ZBP/78dvqaQgtZ9ZpI98RhSmRSpqLBBSMH8ex/hqqt+hu8Hu03l2NbYkhOzqfF98slnOWonrmckHLJzZtI9UGDOUQfR//hCGsUSYrDIgw8+yU033T4Cd737MxJVqDtKX98gnzzna5xyyhtJpZJc891f8h8feBtHfOVs0jMms2ywyIQLP86qvkG++tEvb7FgJp/PcdWVX6Cru4d7L/vhdo0ZwMCiZc3UBIAKQoQhX/KaH1GD5vsBqYnjdui14484gAmnnsynPvsNHZKSgvxe09nvjPfQ++QieIVr3e1qwlDRcF0S239pk9S4DlZ29/DVS3/I977+WRZ9/9dsfHQBU096NePGtfHwwyOWDN+j2NlKtFRXJ3ZXB5//0tW8852vZ9qi5QwuW8UTV/+CeWe97xVhzEYaYUhmvPU1LFndzWWX/Yj9Zk1j5S9vojFQYM0d/6LzBcVoMTuOYUhOOunVzYjClqhUqlQqVWbOnMKSpavIHLwvy59YxE033c6qVetwXZdCobTZiXxo3Z9++ruZLQR3X3oNfpRe2B5mKsne//FW3GKZZTfejt2SYcY7XseVN9z6kqqgR9SgPfzwU5z+9c+RmtD5otzPprTMmsohF3yM3/7pTp54YhFSSu64+9+ccurJmIbB5OmTWPqN/xrJWxuzyK1UIb6Q1rmzmPf5M7j6lzexevU6vFodISWTTzgyqpCMB4UOH4WRdBCmgXK3bYisdIpjvnk+f5r/EA8//BTveMeJoBQHf+Y0lt54W7MfbSzg+z7pCTvm4E489jDa3/1GPnHOpdRqDYQhaZ07i32PfjcDi1c0C89idp4jjzyIy75wFutu++cOtZQk8jnSvs+kKRM48eJPUTcMAkOyet3GZkFdqELuuuvfbNzYxzvfegJPffGqHTZmdkuWIy/+FJ0nHo2ou8x8+4nkZkyhu1xl4cJlTJ7cxcSJ45qi7Zu2EgDccMPWU1EjatAef3whtz/4BMdfcR6Pfuta+hcs3ez/pW0x7tD9Oeyrn+bm+Q/yk5/8DwBhGPLd7/6SX/zif2lpyZLNZnjqqWdH8tbGJGvXbmDuMYew4v/u2mYxgpVJs/9H389f7n+MG274K62tOTzbYu5pp+icjxBxiPElsHbtBsL2PPm9ptO/YMlWXycMgzn/750UWjJ873u/wnU9nnlmGSed+V7sXIa5uTQPb+hlrFi1Bx98gg999dOkxndQ3bDlalmA1n1mctAXzuK6P9zGwoXLMAzJ7Xc9wMn/8TYsw6Br5hSWXvKDl/HOxxbFYpl6qMjOmMzSG/7aLNDYEioMKT3XrQ2fUgSui7Qskp1tJNpamq9LdXVy1puORzo2xfkPsfHRBTt8P7npk0i05/H7B7ESDrnpkzFsi/akw7XfuRDLNGCwSFBr4A4UKa7YvIfxNrF153tEi0IAUqkE5513Jm879jDu+8xlzS+409bCcd+9CDltIt/90X9z001/2+WFBKPBSykK2Vn2339vrvvBV3jqku+zdv5DWzRqiY5WDvviRxmcNpFzPn1ZMwZ+2GHzOPjgfZkxYxKu63HVVT/bred5jVZRyA6+B+ed9xFOPnhfHrjwaoor17zob2GmEhz82dNJHnc45573zebgyyFlm0TCYd68ffi///vHy97Yu6vWrG1bfPWr53DsxPE89q2fvsjYGwmbriMP4uCvnM31t87nu9/7VVMhxTQNMpk0ra05UqkkCxcuHZWG/JfIbqPluNde0zjppFdz2KHz2JbD1JLL0p5JocKAhG3jrlrLwDPLtFh6hF+rR4cVRa1ngOqGXuo7WHxjODbStvArNaxsGmmZhJ6PERW/ScvEjiq9U12deorDC75LX390AStLlV1f5di8aUPyuc+dwes727j3vG8C+gt90u+/y/X/fIirr/7FmM0RvJwGTQgtEnrx+Wey9sbbeerH/91URXHaWphy4jHMevcbeXhjH5df/l+7hQLCcNmdDRpAImFz/vlncfKJR/PA569gY9ScK6Rkn/98OzNOfh3Lag0u+sp3Wb6jqhkvE7tyzaZSSc477yO89dhDuf/Tl9H/jI7aJDvbOO77Xybo6uSq7/2SW265a7tVta9AdhuDtsm1t/n/lmU2Q3z5fAtHHXUQLS2ZzV4zY8ZkOjtakdJg3t7TWX39X3jyB7/Zofe30inmnnYKC352A6lxHRz82dN4+trrOejcD2Nk0phJBz+VxFeKNRv7qddffJr82qU/ZOXKtbu+yjGTSXHkkQeycWMfqVRiM/UKv1pn4S9u5OB3v2kk33KPRim49dZ72LixjysuPZdpK9ew8v/uAiDR2sKhF32Cn/zif7n22uupVncsvh0zPOp1l29848csX76aT130Se54/2fwa3VUGNJx0FyW1Op85jNfH+0y8pedarXGZZf9EO8LZ3H8B9/B/Rd+G9D7gZVJ8z8338Gf/vT3eKjny8T2nrPres0excHB0lY1OkEbx3PPPY0TNml83x7SsZj1ztcz8cSjaZk6AcO2WX3HvWQOmMOll/+E5ctX093dQ61Wp1qt7bQIxogZNCHg858/g/e/9fW4QuGjCJ7rxs5ncQdLSNui6+iDeXJ9T7x4R4ghPcVHH32GJxcuY8qEzub/ldduYMN9j5JI2LExexkYP74dEKxcuVbrr2yyxhf+6iYO/8FXNpv8sCeQy2U4+uiD6e7eSCaT3kydxatUWfSrmzj4LSeM3g3GvCSUUlqFaRP91u1hpZJ4psnXfnoDn/vM/6Pw578z+OwK+u55kJkzJ/PHP+6YwPrWGMETmmD69MmUnlmDCkKkbZEYl+fwCz9O75PP0r7fXqSPOIDvnXp+bNBGACEE73//W/jgf76dpxcsYd+5syhukqMIXJfSyrWkM6lRvMs9g8MOm8f3rr4QyzJZvXYDybYWkh2tlCPRVjub2eNK8YUQXPDFj/LO1x+PJxWBFLgrnuOZn92IWyhhODYTjj2UB9ZtZKwUweypiB101OxchsO+9HHmP/wU8+c/yMc/8h4Gl6xi4vGHU1iyCiOf3f5FtsOIGTSlFCtWrOGYd5xE733P4qQchCFx99uLtVKyFrjzmz/drZSZX8kkEg6nf/gU8hvrvO2YoxBS4J/6TrrvfYR6f4H8XtMZ96bj+eNnvzHatzrmOeSQfcnVFZVn1jJ3zkTCms8hn/8IT/3X72jbby9mv+dNXPvbPzUlgvYEhBBMnTqR4gKdLxSGJNnVxuFf+gQDi5bRtu9srHn7cM0HP/eKGuAbszl9fQO0nXBks7hjawgpmfH2E+kf18Elp32BRsOj4QfMPuUkWmZPo+fRBYTrX/r4qhEMOQpmzJhMeel6vIEKRtLGndLCR0/9cmzEdgFBEFAolmlPpCguXENQbZDbdzIn/Pxy3GodM5Pmf//vH001i5hdx+rV67C78pSXbqC2pp/QD+g68RjqM6cgTINHlz/HzTffuUdFJsIwZMXKNRz2ptfSd/9inM4c0jap7D2d5WHAMs/njq//aItqODGvHB544HH8sz/E1De8mpV/vWuLh21hGuz1njcx46z38cWvfLcpFn/ZN37MKaecRK5ap2tyF3/eQYm0bTGiRSFSCNz+slbCHqxQK1bo69uzkuAvJ1JK7NYM1VU9tMybSqPF4YKLrmbx4pWAoru7Z48Kc40W48Z1EFYahK6HOxjSccJ+XP7tn/K7392CUoogCMdiBd82kVIyY/pkyou7cfvLmCmHAeHzsY99hfUj4InH7B50d/fwla9dw+UXn03r3Jk88b3nh9tK26J9/72Y8dbXYh51EOdf9B3mz3+o+buPP76Qxx9f2By8OhJtXKOm5Rjz0jAMg1wmxeBjK/HLdaqre1m0vs7f/37fK7Ff5xVNImHT2FjEG6yCFDQKFR588IkRnbP3SkQIgTtQhlDhDlYolxLNUS0xY4d77nmQsz//Tb528aeYO1hiwXU3ALrn7NirLuDhFc/xjU99bbPpD5sShuGIOd4jXnYl7dhGvqxEYSwVhCil4nzEaBM//5g9DCHg0UcX8L8330HHQXObP/erNdb98yE8z9/iKJxdwchaHyEwknpemplNUms04tNCzB6B2ImpB3sMQoedYsYu++23F+d86lTWdW+ks7MNt1DSFk4pVBDSfd9jdHzkPUgpeDmyHyNr0JTCK2j5JMOxWL7iuT0+7LIrEYbEbsvgl+v6ZKziCQWjhZVPgxRI0wDL2KVT0V8pCMBIaINm5VKUa7U4pzvG+PjHP8BRU6ZjztkHsyVN6DVYdvMd9D6xiFRXB/ue9T6uu3X+y5ZDHvn4oBRIxyI1YxwrHv33iF8+5nlUEOIO6um7Vj7Nsw89vUdV0u1OuP06VyQsg4Fy+RUtMzZSKAVeMXJwExbLly8fk/qtu4qZM6fw9refyIoVa7jrrgea1YG7E7VaAxQUnlqNtEys1jTHfe/LlNauJz1xHEvWbuQPf7j1ZUuFjLhBk7aJ3Z5hUHn8/ve3jPTlY16IUiAEVi65R/U57ZZIQWJcCxsq1aZ80J6OkBKZsEjN6GTZP+8e7dt5xZBOJ/nmFecxt7MLM5fkHye9ms9//nKq21DKHw2q1RrJia2Ul63HGd9CYnonv/j9n/jHPx4AFKtXr6NQKL1s97NLKjiEELiuqwd3xuxSjJSDmUlSdODOO+8d7dvZcxHgdGRJzR7Pz7/9E+rxgFoApGPitGfpbdT4wx+2PscqZnNOP/3d7Dd1Cr3/WIB0LF513IF0dLSyenX3aN/aZnR1dTL4+Eq8gQqVIKSUt/nJT35PoTA6p8kRrXKs113S0zppOXAaPf2DL9sY8T0ZaRpI22Tl6rWsXLl2tG9nz0YIQqVYtmz3UtMfdQQ0XI9abfc6XeyumKbBqR94OwP/Xkro+oSejy0khx66/2jf2hYZmvCh/JAwCEY1fzyi0lff+e4vKJz+bpYsWcXtt8+PC0J2OQKZsLCyScJSfBoeLcJQYWYTpKd1QsJqzvTa06nVG6RnTcbMJFiycHFcKLMTCLSBAAjrHrUVGzn++CP405/ujCvHt8GIhhwXLlzGedH8s5hdi+t6PPDQE7zjLa9hfU8fv/2vP8cVZKPEnXfex+tOPBrfD7j99zeyePGK0b6lUScMQ6666jpOPfWdPPvscv72t3/FecUdxPcDHnjkKY6eOJnSs9pRra0d4LhjDmXWrKksWbJqlO9wc+y2DLW1/QhDbnfe2q4m7oJ+hRIEAZdd9iOuu+4PbNzYF4+IGUVWrlzDh049jzBUe5zE1bZYuHAZF1xw1WjfxiuSdd090Dml+W+vUCFfD5kyZeJuZ9C8ot57rFyS5zb2jmpkbs8a0DTGqNcbrFy5JjZmuwGe58fGLGbEKJcrOONbIGrYl44FSWuLE5xHGxXVShhph/7+wqi2ZsQGLSYmJmY34/rr/8qaWon2o/ZCGJLs3hN4cslyHnlkwWjf2osQloHVmiYxezy33TZ/VO8lNmgxMTExuxkbNvRy0Ve+Ay1JhGVgTGzlyquu2y0L7YSUGAmbwUplMzX90SA2aDExMTG7IT09/c3WpyAI6OnpH+U72jLCkJgZB4QYdaWi2KDFxMTE7KYIQyKkwDFNpk2bNNq38yIWL15By0HTaD1iNv+Y/+9Rz+eLnbGoQogeYPcqsdm9mKaU6tzZX4qf63YZ1nOF+NnuAPGa3XXEz3bXsNXnulMGLSYmJiYmZnclDjnGxMTExIwJYoMWExMTEzMmiA1aTExMTMyYIDZoMTExMTFjgtigxcTExMSMCWKDFhMTExMzJogNWkxMTEzMmCA2aDExMTExY4LYoMXExMTEjAn+P+YA6guGtDS3AAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 540x216 with 10 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "def voc_rand_crop(feature, label, height, width):\n",
    "    \"\"\"随机裁剪特征和标签图像。\"\"\"\n",
    "    rect = torchvision.transforms.RandomCrop.get_params(\n",
    "        feature, (height, width))\n",
    "    feature = torchvision.transforms.functional.crop(feature, *rect)\n",
    "    label = torchvision.transforms.functional.crop(label, *rect)\n",
    "    return feature, label\n",
    "\n",
    "imgs = []\n",
    "for _ in range(n):\n",
    "    imgs += voc_rand_crop(train_features[0], train_labels[0], 200, 300)\n",
    "\n",
    "imgs = [img.permute(1, 2, 0) for img in imgs]\n",
    "d2l.show_images(imgs[::2] + imgs[1::2], 2, n);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "自定义语义分割数据集类"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "origin_pos": 25,
    "tab": [
     "pytorch"
    ]
   },
   "outputs": [],
   "source": [
    "class VOCSegDataset(torch.utils.data.Dataset):\n",
    "    \"\"\"一个用于加载VOC数据集的自定义数据集。\"\"\"\n",
    "    def __init__(self, is_train, crop_size, voc_dir):\n",
    "        self.transform = torchvision.transforms.Normalize(\n",
    "            mean=[0.485, 0.456, 0.406], std=[0.229, 0.224, 0.225])\n",
    "        self.crop_size = crop_size\n",
    "        features, labels = read_voc_images(voc_dir, is_train=is_train)\n",
    "        self.features = [\n",
    "            self.normalize_image(feature)\n",
    "            for feature in self.filter(features)]\n",
    "        self.labels = self.filter(labels)\n",
    "        self.colormap2label = voc_colormap2label()\n",
    "        print('read ' + str(len(self.features)) + ' examples')\n",
    "\n",
    "    def normalize_image(self, img):\n",
    "        return self.transform(img.float())\n",
    "\n",
    "    def filter(self, imgs):\n",
    "        return [\n",
    "            img for img in imgs if (img.shape[1] >= self.crop_size[0] and\n",
    "                                    img.shape[2] >= self.crop_size[1])]\n",
    "\n",
    "    def __getitem__(self, idx):\n",
    "        feature, label = voc_rand_crop(self.features[idx], self.labels[idx],\n",
    "                                       *self.crop_size)\n",
    "        return (feature, voc_label_indices(label, self.colormap2label))\n",
    "\n",
    "    def __len__(self):\n",
    "        return len(self.features)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "读取数据集"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "origin_pos": 27,
    "tab": [
     "pytorch"
    ]
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "read 1114 examples\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "read 1078 examples\n"
     ]
    }
   ],
   "source": [
    "crop_size = (320, 480)\n",
    "voc_train = VOCSegDataset(True, crop_size, voc_dir)\n",
    "voc_test = VOCSegDataset(False, crop_size, voc_dir)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "origin_pos": 30,
    "tab": [
     "pytorch"
    ]
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "torch.Size([64, 3, 320, 480])\n",
      "torch.Size([64, 320, 480])\n"
     ]
    }
   ],
   "source": [
    "batch_size = 64\n",
    "train_iter = torch.utils.data.DataLoader(\n",
    "    voc_train, batch_size, shuffle=True, drop_last=True,\n",
    "    num_workers=d2l.get_dataloader_workers())\n",
    "for X, Y in train_iter:\n",
    "    print(X.shape)\n",
    "    print(Y.shape)\n",
    "    break"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "整合所有组件"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "origin_pos": 33,
    "tab": [
     "pytorch"
    ]
   },
   "outputs": [],
   "source": [
    "def load_data_voc(batch_size, crop_size):\n",
    "    \"\"\"加载VOC语义分割数据集。\"\"\"\n",
    "    voc_dir = d2l.download_extract('voc2012',\n",
    "                                   os.path.join('VOCdevkit', 'VOC2012'))\n",
    "    num_workers = d2l.get_dataloader_workers()\n",
    "    train_iter = torch.utils.data.DataLoader(\n",
    "        VOCSegDataset(True, crop_size, voc_dir), batch_size, shuffle=True,\n",
    "        drop_last=True, num_workers=num_workers)\n",
    "    test_iter = torch.utils.data.DataLoader(\n",
    "        VOCSegDataset(False, crop_size, voc_dir), batch_size, drop_last=True,\n",
    "        num_workers=num_workers)\n",
    "    return train_iter, test_iter"
   ]
  }
 ],
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  "language_info": {
   "name": "python"
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   "overlay": "<div class='my-top-right'><img height=80px src='http://d2l.ai/_static/logo-with-text.png'/></div><div class='my-top-left'></div>",
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 },
 "nbformat": 4,
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}